Pavideoge: A Metadata Markup Video Structure in Video Search Engine

Abstract: In this paper, we study the problems of video processing in video search engine. Video has now become a very important kind of data in Internet; while searching for video is still a challenging task due to the inner properties of video: requiring enormous storage space, being independent, expressing information hiddenly. To handle the properties of video more effectively, in this paper, we propose a new video processing method in video search engine. In detail, the core of the new video processing method is creating pavideoge--a new data type, which contains the video advantages and webpage advantages. The pavideoge has four attributes: real link, videorank, text information and playnum. Each of them combines video's properties with webpage's. Video search engine based on the pavideoge can retrieve video more effectively. The experiment results show the encouraging performance of our approach. Based on the pavideoge, our video search engine can retrieve more precise videos in comparsion with previous related work.


Hierarchical Routing over Dynamic Wireless Networks

Abstract: Wireless network topologies change over time and maintaining routes requires frequent updates. Updates are costly in terms of consuming throughput available for data transmission, which is precious in wireless networks. In this paper, we ask whether there exist low-overhead schemes that produce low-stretch routes. This is studied by using the underlying geometric properties of the connectivity graph in wireless networks.


On the Interesting World of Fractals and Their Applications to Music

Abstract: In this paper we have defined one function that has been used to construct different fractals having fractal dimensions between 1.58 and 2. Also, we tried to calculate the amount of increment of fractal dimension in accordance with the base of the number systems. Further, interestingly enough, these very fractals could be a frame of lyrics for the musicians, as we know that the fractal dimension of music is around 1.65 and varies between a high of 1.68 and a low of 1.60. Further, at the end we conjecture that the switching from one music fractal to another is nothing but enhancing a constant amount fractal dimension which might be equivalent to a kind of different sets of musical notes in various orientations.


Simple implementation of deletion from open-address hash table

Abstract: Deletion from open-address hash table is not so easy as deletion from chained hash table, because in open-address table we can't simply mark a slot containing deleted key as empty. Search for keys may become incorrect. The classical method to implement deletion is to mark slots in hash table by three values: "free", "busy", "deleted". That method is easy to implement, but there are some disadvantages. In this article we consider alternative method of deletion keys, where we avoid using the mark "deleted". The article contains the implementation of the method in Java.


Reducing Network Traffic in Unstructured P2P Systems Using Top-k Queries

Abstract: A major problem of unstructured P2P systems is their heavy network traffic. This is caused mainly by high numbers of query answers, many of which are irrelevant for users. One solution to this problem is to use Top-k queries whereby the user can specify a limited number (k) of the most relevant answers. In this paper, we present FD, a (Fully Distributed) framework for executing Top-k queries in unstructured P2P systems, with the objective of reducing network traffic. FD consists of a family of algorithms that are simple but effec-tive. FD is completely distributed, does not depend on the existence of certain peers, and addresses the volatility of peers during query execution. We vali-dated FD through implementation over a 64-node cluster and simulation using the BRITE topology generator and SimJava. Our performance evaluation shows that FD can achieve major performance gains in terms of communication and response time.


Reference Resolution within the Framework of Cognitive Grammar

Abstract: Following the principles of Cognitive Grammar, we concentrate on a model for reference resolution that attempts to overcome the difficulties previous approaches, based on the fundamental assumption that all reference (independent on the type of the referring expression) is accomplished via access to and restructuring of domains of reference rather than by direct linkage to the entities themselves. The model accounts for entities not explicitly mentioned but understood in a discourse, and enables exploitation of discursive and perceptual context to limit the set of potential referents for a given referring expression. As the most important feature, we note that a single mechanism is required to handle what are typically treated as diverse phenomena. Our approach, then, provides a fresh perspective on the relations between Cognitive Grammar and the problem of reference.


Singularity of Sparse Circulant Matrices is NP-complete

Abstract: It is shown by Karp reduction that deciding the singularity of $(2^n - 1) \times (2^n - 1)$ sparse circulant matrices (SC problem) is NP-complete. We can write them only implicitly, by indicating values of the $2 + n(n + 1)/2$ eventually nonzero entries of the first row and can make all matrix operations with them. The positions are $0, 1, 2^{i} + 2^{j}$. The complexity parameter is $n$. Mulmuley's work on the rank of matrices \cite{Mulmuley87} makes SC stand alone in a list of 3,000 and growing NP-complete problems.


Memory Consistency Conditions for Self-Assembly Programming

Abstract: Perhaps the two most significant theoretical questions about the programming of self-assembling agents are: (1) necessary and sufficient conditions to produce a unique terminal assembly, and (2) error correction. We address both questions, by reducing two well-studied models of tile assembly to models of distributed shared memory (DSM), in order to obtain results from the memory consistency systems induced by tile assembly systems when simulated in the DSM setting. The Abstract Tile Assembly Model (aTAM) can be simulated by a DSM system that obeys causal consistency, and the locally deterministic tile assembly systems in the aTAM correspond exactly to the concurrent-write free programs that simulate tile assembly in such a model. Thus, the detection of the failure of local determinism (which had formerly been an open problem) reduces to the detection of data races in simulating programs. Further, the Kinetic Tile Assembly Model can be simulated by a DSM system that obeys GWO, a memory consistency condition defined by Steinke and Nutt. (To our knowledge, this is the first natural example of a DSM system that obeys GWO, but no stronger consistency condition.) We combine these results with the observation that self-assembly algorithms are local algorithms, and there exists a fast conversion of deterministic local algorithms into deterministic self-stabilizing algorithms. This provides an "immediate" generalization of a theorem by Soloveichik et al. about the existence of tile assembly systems that simultaneously perform two forms of self-stabilization: proofreading and self-healing. Our reductions and proof techniques can be extended to the programming of self-assembling agents in a variety of media, not just DNA tiles, and not just two-dimensional surfaces.


Measurement and Analysis of an Online Content Voting Network: A Case Study of Digg

Abstract: Emergence of online content voting networks allows users to share and rate content including social news, photos and videos. The basic idea behind online content voting networks is that aggregate user activities (e.g., submitting and rating content) makes high-quality content thrive through the unprecedented scale, high dynamics and divergent quality of user generated content (UGC). To better understand the nature and impact of online content voting networks, we have analyzed Digg, a popular online social news aggregator and rating website. Based on a large amount of data collected, we provide an in-depth study of Digg. In particular, we study structural properties of Digg social network, impact of social network properties on user digging activities and vice versa, distribution of user diggs, content promotion, and information filtering. We also provide insight into design of content promotion algorithms and recommendation-assisted content discovery. Overall, we believe that the results presented in this paper are crucial in understanding online content rating networks.


Marking-up multiple views of a Text: Discourse and Reference

Abstract: We describe an encoding scheme for discourse structure and reference, based on the TEI Guidelines and the recommendations of the Corpus Encoding Specification (CES). A central feature of the scheme is a CES-based data architecture enabling the encoding of and access to multiple views of a marked-up document. We describe a tool architecture that supports the encoding scheme, and then show how we have used the encoding scheme and the tools to perform a discourse analytic task in support of a model of global discourse cohesion called Veins Theory (Cristea & Ide, 1998).


A Common XML-based Framework for Syntactic Annotations

Abstract: It is widely recognized that the proliferation of annotation schemes runs counter to the need to re-use language resources, and that standards for linguistic annotation are becoming increasingly mandatory. To answer this need, we have developed a framework comprised of an abstract model for a variety of different annotation types (e.g., morpho-syntactic tagging, syntactic annotation, co-reference annotation, etc.), which can be instantiated in different ways depending on the annotator's approach and goals. In this paper we provide an overview of the framework, demonstrate its applicability to syntactic annotation, and show how it can contribute to comparative evaluation of parser output and diverse syntactic annotation schemes.


Standards for Language Resources

Abstract: This paper presents an abstract data model for linguistic annotations and its implementation using XML, RDF and related standards; and to outline the work of a newly formed committee of the International Standards Organization (ISO), ISO/TC 37/SC 4 Language Resource Management, which will use this work as its starting point. The primary motive for presenting the latter is to solicit the participation of members of the research community to contribute to the work of the committee.


Dynamically Generated Interfaces in XML Based Architecture

Abstract: Providing on-line services on the Internet will require the definition of flexible interfaces that are capable of adapting to the user's characteristics. This is all the more important in the context of medical applications like home monitoring, where no two patients have the same medical profile. Still, the problem is not limited to the capacity of defining generic interfaces, as has been made possible by UIML, but also to define the underlying information structures from which these may be generated. The DIATELIC project deals with the tele-monitoring of patients under peritoneal dialysis. By means of XML abstractions, termed as "medical components", to represent the patient's profile, the application configures the customizable properties of the patient's interface and generates a UIML document dynamically. The interface allows the patient to feed the data manually or use a device which allows "automatic data acquisition". The acquired medical data is transferred to an expert system, which analyses the data and sends alerts to the medical staff. In this paper we show how UIML can be seen as one component within a global XML based architecture.


An Optimal Labeling Scheme for Ancestry Queries

Abstract: An ancestry labeling scheme assigns labels (bit strings) to the nodes of rooted trees such that ancestry queries between any two nodes in a tree can be answered merely by looking at their corresponding labels. The quality of an ancestry labeling scheme is measured by its label size, that is the maximal number of bits in a label of a tree node. In addition to its theoretical appeal, the design of efficient ancestry labeling schemes is motivated by applications in web search engines. For this purpose, even small improvements in the label size are important. In fact, the literature about this topic is interested in the exact label size rather than just its order of magnitude. As a result, following the proposal of a simple interval-based ancestry scheme with label size $2\log_2 n$ bits (Kannan et al., STOC '88), a considerable amount of work was devoted to improve the bound on the size of a label. The current state of the art upper bound is $\log_2 n + O(\sqrt{\log n})$ bits (Abiteboul et al., SODA '02) which is still far from the known $\log_2 n + \Omega(\log\log n)$ bits lower bound (Alstrup et al., SODA '03). In this paper we close the gap between the known lower and upper bounds, by constructing an ancestry labeling scheme with label size $\log_2 n + O(\log\log n)$ bits. In addition to the optimal label size, our scheme assigns the labels in linear time and can support any ancestry query in constant time.


On disjoint matchings in cubic graphs: maximum 2- and 3-edge-colorable subgraphs

Abstract: We show that any $2-$factor of a cubic graph can be extended to a maximum $3-$edge-colorable subgraph. We also show that the sum of sizes of maximum $2-$ and $3-$edge-colorable subgraphs of a cubic graph is at least twice of its number of vertices. Finally, for a cubic graph $G$, consider the pairs of edge-disjoint matchings whose union consists of as many edges as possible. Let $H$ be the largest matching among such pairs. Let $M$ be a maximum matching of $G$. We show that 9/8 is a tight upper bound for $|M|/|H|$.


Crossing-Free Acyclic Hamiltonian Path Completion for Planar st-Digraphs

Abstract: In this paper we study the problem of existence of a crossing-free acyclic hamiltonian path completion (for short, HP-completion) set for embedded upward planar digraphs. In the context of book embeddings, this question becomes: given an embedded upward planar digraph $G$, determine whether there exists an upward 2-page book embedding of $G$ preserving the given planar embedding. Given an embedded $st$-digraph $G$ which has a crossing-free HP-completion set, we show that there always exists a crossing-free HP-completion set with at most two edges per face of $G$. For an embedded $N$-free upward planar digraph $G$, we show that there always exists a crossing-free acyclic HP-completion set for $G$ which, moreover, can be computed in linear time. For a width-$k$ embedded planar $st$-digraph $G$, we show that we can be efficiently test whether $G$ admits a crossing-free acyclic HP-completion set.


Enhanced sampling schemes for MCMC based blind Bernoulli-Gaussian deconvolution

Abstract: This paper proposes and compares two new sampling schemes for sparse deconvolution using a Bernoulli-Gaussian model. To tackle such a deconvolution problem in a blind and unsupervised context, the Markov Chain Monte Carlo (MCMC) framework is usually adopted, and the chosen sampling scheme is most often the Gibbs sampler. However, such a sampling scheme fails to explore the state space efficiently. Our first alternative, the $K$-tuple Gibbs sampler, is simply a grouped Gibbs sampler. The second one, called partially marginalized sampler, is obtained by integrating the Gaussian amplitudes out of the target distribution. While the mathematical validity of the first scheme is obvious as a particular instance of the Gibbs sampler, a more detailed analysis is provided to prove the validity of the second scheme. For both methods, optimized implementations are proposed in terms of computation and storage cost. Finally, simulation results validate both schemes as more efficient in terms of convergence time compared with the plain Gibbs sampler. Benchmark sequence simulations show that the partially marginalized sampler takes fewer iterations to converge than the $K$-tuple Gibbs sampler. However, its computation load per iteration grows almost quadratically with respect to the data length, while it only grows linearly for the $K$-tuple Gibbs sampler.


Graph-based data clustering: a quadratic-vertex problem kernel for s-Plex Cluster Vertex Deletion

Abstract: We introduce the s-Plex Cluster Vertex Deletion problem. Like the Cluster Vertex Deletion problem, it is NP-hard and motivated by graph-based data clustering. While the task in Cluster Vertex Deletion is to delete vertices from a graph so that its connected components become cliques, the task in s-Plex Cluster Vertex Deletion is to delete vertices from a graph so that its connected components become s-plexes. An s-plex is a graph in which every vertex is nonadjacent to at most s-1 other vertices; a clique is an 1-plex. In contrast to Cluster Vertex Deletion, s-Plex Cluster Vertex Deletion allows to balance the number of vertex deletions against the sizes and the density of the resulting clusters, which are s-plexes instead of cliques. The focus of this work is the development of provably efficient and effective data reduction rules for s-Plex Cluster Vertex Deletion. In terms of fixed-parameter algorithmics, these yield a so-called problem kernel. A similar problem, s-Plex Editing, where the task is the insertion or the deletion of edges so that the connected components of a graph become s-plexes, has also been studied in terms of fixed-parameter algorithmics. Using the number of allowed graph modifications as parameter, we expect typical parameter values for s-Plex Cluster Vertex Deletion to be significantly lower than for s-Plex Editing, because one vertex deletion can lead to a high number of edge deletions. This holds out the prospect for faster fixed-parameter algorithms for s-Plex Cluster Vertex Deletion.


Efficient Quality-Based Playout Buffer Algorithm

Abstract: Playout buffers are used in VoIP systems to compensate for network delay jitter by making a trade-off between delay and loss. In this work we propose a playout buffer algorithm that makes the trade-off based on maximization of conversational speech quality, aiming to keep the computational complexity lowest possible. We model the network delay using a Pareto distribution and show that it is a good compromise between providing an appropriate fit to the network delay characteristics and yielding a low arithmetical complexity. We use the ITU-T E-Model as the quality model and simplify its delay impairment function. The proposed playout buffer algorithm finds the optimum playout delay using a closed-form solution that minimizes the sum of the simplified delay impairment factor and the loss-dependent equipment impairment factor of the E-model. The simulation results show that our proposed algorithm outperforms existing state-of-the-art algorithms with a reduced complexity for a quality-based algorithm.


A progression ring for interfaces of instruction sequences, threads, and services

Abstract: We define focus-method interfaces and some connections between such interfaces and instruction sequences, giving rise to instruction sequence components. We provide a flexible and practical notation for interfaces using an abstract datatype specification comparable to that of basic process algebra with deadlock. The structures thus defined are called progression rings. We also define thread and service components. Two types of composition of instruction sequences or threads and services (called `use' and `apply') are lifted to the level of components.


The Asymmetric Traveling Salesman Problem on Graphs with Bounded Genus

Abstract: We give a constant factor approximation algorithm for the asymmetric traveling salesman problem when the support graph of the solution of the Held-Karp linear programming relaxation has bounded orientable genus.


A new efficient k-out-of-n Oblivious Transfer protocol

Abstract: This paper presents a new efficient protocol for k-out-of-n oblivious transfer which is a generalization of Parakh's 1-out-of-2 oblivious transfer protocol based on Diffie-Hellman key exchange. In the proposed protocol, the parties involved generate Diffie-Hellman keys obliviously and then use them for oblivious transfer of secrets.


Electric routing and concurrent flow cutting

Abstract: We investigate an oblivious routing scheme, amenable to distributed computation and resilient to graph changes, based on electrical flow. Our main technical contribution is a new rounding method which we use to obtain a bound on the L1->L1 operator norm of the inverse graph Laplacian. We show how this norm reflects both latency and congestion of electric routing.


Going Off-road: Transversal Complexity in Road Networks

Abstract: A geometric graph is a graph embedded in the plane with vertices at points and edges drawn as curves (which are usually straight line segments) between those points. The average transversal complexity of a geometric graph is the number of edges of that graph that are crossed by random line or line segment. In this paper, we study the average transversal complexity of road networks. By viewing road networks as multiscale-dispersed graphs, we show that a random line will cross the edges of such a graph O(sqrt(n)) times on average. In addition, we provide by empirical evidence from experiments on the road networks of the fifty states of United States and the District of Columbia that this bound holds in practice and has a small constant factor. Combining this result with data structuring techniques from computational geometry, allows us to show that we can then do point location and ray-shooting navigational queries with respect to road networks in O(sqrt(n) log n) expected time. Finally, we provide empirical justification for this claim as well.


Distribution-Specific Agnostic Boosting

Abstract: We consider the problem of boosting the accuracy of weak learning algorithms in the agnostic learning framework of Haussler (1992) and Kearns et al. (1992). Known algorithms for this problem (Ben-David et al., 2001; Gavinsky, 2002; Kalai et al., 2008) follow the same strategy as boosting algorithms in the PAC model: the weak learner is executed on the same target function but over different distributions on the domain. We demonstrate boosting algorithms for the agnostic learning framework that only modify the distribution on the labels of the points (or, equivalently, modify the target function). This allows boosting a distribution-specific weak agnostic learner to a strong agnostic learner with respect to the same distribution. When applied to the weak agnostic parity learning algorithm of Goldreich and Levin (1989) our algorithm yields a simple PAC learning algorithm for DNF and an agnostic learning algorithm for decision trees over the uniform distribution using membership queries. These results substantially simplify Jackson's famous DNF learning algorithm (1994) and the recent result of Gopalan et al. (2008). We also strengthen the connection to hard-core set constructions discovered by Klivans and Servedio (1999) by demonstrating that hard-core set constructions that achieve the optimal hard-core set size (given by Holenstein (2005) and Barak et al. (2009)) imply distribution-specific agnostic boosting algorithms. Conversely, our boosting algorithm gives a simple hard-core set construction with an (almost) optimal hard-core set size.


A Convergent Online Single Time Scale Actor Critic Algorithm

Abstract: Actor-Critic based approaches were among the first to address reinforcement learning in a general setting. Recently, these algorithms have gained renewed interest due to their generality, good convergence properties, and possible biological relevance. In this paper, we introduce an online temporal difference based actor-critic algorithm which is proved to converge to a neighborhood of a local maximum of the average reward. Linear function approximation is used by the critic in order estimate the value function, and the temporal difference signal, which is passed from the critic to the actor. The main distinguishing feature of the present convergence proof is that both the actor and the critic operate on a similar time scale, while in most current convergence proofs they are required to have very different time scales in order to converge. Moreover, the same temporal difference signal is used to update the parameters of both the actor and the critic. A limitation of the proposed approach, compared to results available for two time scale convergence, is that convergence is guaranteed only to a neighborhood of an optimal value, rather to an optimal value itself. The single time scale and identical temporal difference signal used by the actor and the critic, may provide a step towards constructing more biologically realistic models of reinforcement learning in the brain.


Language Models for Handwritten Short Message Services

Abstract: Handwriting is an alternative method for entering texts composing Short Message Services. However, a whole new language features the texts which are produced. They include for instance abbreviations and other consonantal writing which sprung up for time saving and fashion. We have collected and processed a significant number of such handwriting SMS, and used various strategies to tackle this challenging area of handwriting recognition. We proposed to study more specifically three different phenomena: consonant skeleton, rebus, and phonetic writing. For each of them, we compare the rough results produced by a standard recognition system with those obtained when using a specific language model.


Vers la reconnaissance de mini-messages manuscrits

Abstract: Handwriting is an alternative method for entering texts which composed Short Message Services. However, a whole new language features the texts which are produced. They include for instance abbreviations and other consonantal writing which sprung up for time saving and fashion. We have collected and processed a significant number of such handwritten SMS, and used various strategies to tackle this challenging area of handwriting recognition. We proposed to study more specifically three different phenomena: consonant skeleton, rebus, and phonetic writing. For each of them, we compare the rough results produced by a standard recognition system with those obtained when using a specific language model to take care of them.


ALOHA With Collision Resolution(ALOHA-CR): Theory and Software Defined Radio Implementation

Abstract: A cross-layer scheme, namely ALOHA With Collision Resolution (ALOHA-CR), is proposed for high throughput wireless communications in a cellular scenario. Transmissions occur in a time-slotted ALOHA-type fashion but with an important difference: simultaneous transmissions of two users can be successful. If more than two users transmit in the same slot the collision cannot be resolved and retransmission is required. If only one user transmits, the transmitted packet is recovered with some probability, depending on the state of the channel. If two users transmit the collision is resolved and the packets are recovered by first over-sampling the collision signal and then exploiting independent information about the two users that is contained in the signal polyphase components. The ALOHA-CR throughput is derived under the infinite backlog assumption and also under the assumption of finite backlog. The contention probability is determined under these two assumptions in order to maximize the network throughput and maintain stability. Queuing delay analysis for network users is also conducted. The performance of ALOHA-CR is demonstrated on the Wireless Open Access Research Platform (WARP) test-bed containing five software defined radio nodes. Analysis and test-bed results indicate that ALOHA-CR leads to significant increase in throughput and reduction of service delays.


A note on the data-driven capacity of P2P networks

Abstract: We consider two capacity problems in P2P networks. In the first one, the nodes have an infinite amount of data to send and the goal is to optimally allocate their uplink bandwidths such that the demands of every peer in terms of receiving data rate are met. We solve this problem through a mapping from a node-weighted graph featuring two labels per node to a max flow problem on an edge-weighted bipartite graph. In the second problem under consideration, the resource allocation is driven by the availability of the data resource that the peers are interested in sharing. That is a node cannot allocate its uplink resources unless it has data to transmit first. The problem of uplink bandwidth allocation is then equivalent to constructing a set of directed trees in the overlay such that the number of nodes receiving the data is maximized while the uplink capacities of the peers are not exceeded. We show that the problem is NP-complete, and provide a linear programming decomposition decoupling it into a master problem and multiple slave subproblems that can be resolved in polynomial time. We also design a heuristic algorithm in order to compute a suboptimal solution in a reasonable time. This algorithm requires only a local knowledge from nodes, so it should support distributed implementations. We analyze both problems through a series of simulation experiments featuring different network sizes and network densities. On large networks, we compare our heuristic and its variants with a genetic algorithm and show that our heuristic computes the better resource allocation. On smaller networks, we contrast these performances to that of the exact algorithm and show that resource allocation fulfilling a large part of the peer can be found, even for hard configuration where no resources are in excess.


Median K-flats for hybrid linear modeling with many outliers

Abstract: We describe the Median K-Flats (MKF) algorithm, a simple online method for hybrid linear modeling, i.e., for approximating data by a mixture of flats. This algorithm simultaneously partitions the data into clusters while finding their corresponding best approximating l1 d-flats, so that the cumulative l1 error is minimized. The current implementation restricts d-flats to be d-dimensional linear subspaces. It requires a negligible amount of storage, and its complexity, when modeling data consisting of N points in D-dimensional Euclidean space with K d-dimensional linear subspaces, is of order O(n K d D+n d^2 D), where n is the number of iterations required for convergence (empirically on the order of 10^4). Since it is an online algorithm, data can be supplied to it incrementally and it can incrementally produce the corresponding output. The performance of the algorithm is carefully evaluated using synthetic and real data.


On the largest empty axis-parallel box amidst $n$ points

Abstract: We give the first nontrivial upper and lower bounds on the maximum volume of an empty axis-parallel box inside an axis-parallel unit hypercube in $\RR^d$ containing $n$ points. For a fixed $d$, we show that the maximum volume is of the order $\Theta(\frac{1}{n})$. We then use the fact that the maximum volume is $\Omega(\frac{1}{n})$ in our design of the first efficient $(1-\eps)$-approximation algorithm for the following problem: Given an axis-parallel $d$-dimensional box $R$ in $\RR^d$ containing $n$ points, compute a maximum-volume empty axis-parallel $d$-dimensional box contained in $R$. The running time of our algorithm is nearly linear in $n$, for small $d$, and increases only by an $O(\log{n})$ factor when one goes up one dimension. No previous efficient exact or approximation algorithms were known for this problem for $d \geq 4$. As the problem has been recently shown to be NP-hard in arbitrary high dimensions (i.e., when $d$ is part of the input), the existence of efficient exact algorithms is unlikely. We also obtain tight estimates on the maximum volume of an empty axis-parallel hypercube inside an axis-parallel unit hypercube in $\RR^d$ containing $n$ points. For a fixed $d$, this maximum volume is of the same order order $\Theta(\frac{1}{n})$. A faster $(1-\eps)$-approximation algorithm, with a milder dependence on $d$ in the running time, is obtained in this case.


Succinct Representation of Well-Spaced Point Clouds

Abstract: A set of n points in low dimensions takes Theta(n w) bits to store on a w-bit machine. Surface reconstruction and mesh refinement impose a requirement on the distribution of the points they process. I show how to use this assumption to lossily compress a set of n input points into a representation that takes only O(n) bits, independent of the word size. The loss can keep inter-point distances to within 10% relative error while still achieving a factor of three space savings. The representation allows standard quadtree operations, along with computing the restricted Voronoi cell of a point, in time O(w^2 + log n), which can be improved to time O(log n) if w is in Theta(log n). Thus one can use this compressed representation to perform mesh refinement or surface reconstruction in O(n) bits with only a logarithmic slowdown.


The quantitative side of the Repertory Grid Technique: some concerns

Abstract: User experience (UX) evaluation is gaining increased interest lately, both from academia and industry. In this paper we argue that UX evaluation needs to fulfill two important requirements: scalability, i.e. the ability to provide useful feedback in different stages of the design, and diversity, i.e. the ability to reflect the di-versity of opinions that may exist in different users. We promote the use of the Repertory Grid Technique as a promising UX evaluation technique and discuss some of our concerns regarding the quantitative side of its use.


On Low Distortion Embeddings of Statistical Distance Measures into Low Dimensional Spaces

Abstract: Statistical distance measures have found wide applicability in information retrieval tasks that typically involve high dimensional datasets. In order to reduce the storage space and ensure efficient performance of queries, dimensionality reduction while preserving the inter-point similarity is highly desirable. In this paper, we investigate various statistical distance measures from the point of view of discovering low distortion embeddings into low-dimensional spaces. More specifically, we consider the Mahalanobis distance measure, the Bhattacharyya class of divergences and the Kullback-Leibler divergence. We present a dimensionality reduction method based on the Johnson-Lindenstrauss Lemma for the Mahalanobis measure that achieves arbitrarily low distortion. By using the Johnson-Lindenstrauss Lemma again, we further demonstrate that the Bhattacharyya distance admits dimensionality reduction with arbitrarily low additive error. We also examine the question of embeddability into metric spaces for these distance measures due to the availability of efficient indexing schemes on metric spaces. We provide explicit constructions of point sets under the Bhattacharyya and the Kullback-Leibler divergences whose embeddings into any metric space incur arbitrarily large distortions. We show that the lower bound presented for Bhattacharyya distance is nearly tight by providing an embedding that approaches the lower bound for relatively small dimensional datasets.


FPT Algorithms for Connected Feedback Vertex Set

Abstract: We study the recently introduced Connected Feedback Vertex Set (CFVS) problem from the view-point of parameterized algorithms. CFVS is the connected variant of the classical Feedback Vertex Set problem and is defined as follows: given a graph G=(V,E) and an integer k, decide whether there exists a subset F of V, of size at most k, such that G[V F] is a forest and G[F] is connected. We show that Connected Feedback Vertex Set can be solved in time $O(2^{O(k)}n^{O(1)})$ on general graphs and in time $O(2^{O(\sqrt{k}\log k)}n^{O(1)})$ on graphs excluding a fixed graph H as a minor. Our result on general undirected graphs uses as subroutine, a parameterized algorithm for Group Steiner Tree, a well studied variant of Steiner Tree. We find the algorithm for Group Steiner Tree of independent interest and believe that it will be useful for obtaining parameterized algorithms for other connectivity problems.


The Stackelberg Minimum Spanning Tree Game on Planar and Bounded-Treewidth Graphs

Abstract: The Stackelberg Minimum Spanning Tree Game is a two-level combinatorial pricing problem played on a graph representing a network. Its edges are colored either red or blue, and the red edges have a given fixed cost, representing the competitor's prices. The first player chooses an assignment of prices to the blue edges, and the second player then buys the cheapest spanning tree, using any combination of red and blue edges. The goal of the first player is to maximize the total price of purchased blue edges. We study this problem in the cases of planar and bounded-treewidth graphs. We show that the problem is NP-hard on planar graphs but can be solved in polynomial time on graphs of bounded treewidth.


Topology of 2D and 3D Rational Curves

Abstract: In this paper we present algorithms for computing the topology of planar and space rational curves defined by a parametrization. The algorithms given here work directly with the parametrization of the curve, and do not require to compute or use the implicit equation of the curve (in the case of planar curves) or of any projection (in the case of space curves). Moreover, these algorithms have been implemented in Maple; the examples considered and the timings obtained show good performance skills.


Decomposition of the NVALUE constraint

Abstract: We study decompositions of NVALUE, a global constraint that can be used to model a wide range of problems where values need to be counted. Whilst decomposition typically hinders propagation, we identify one decomposition that maintains a global view as enforcing bound consistency on the decomposition achieves bound consistency on the original global NVALUE constraint. Such decompositions offer the prospect for advanced solving techniques like nogood learning and impact based branching heuristics. They may also help SAT and IP solvers take advantage of the propagation of global constraints.


Symmetries of Symmetry Breaking Constraints

Abstract: Symmetry is an important feature of many constraint programs. We show that any symmetry acting on a set of symmetry breaking constraints can be used to break symmetry. Different symmetries pick out different solutions in each symmetry class. We use these observations in two methods for eliminating symmetry from a problem. These methods are designed to have many of the advantages of symmetry breaking methods that post static symmetry breaking constraint without some of the disadvantages. In particular, the two methods prune the search space using fast and efficient propagation of posted constraints, whilst reducing the conflict between symmetry breaking and branching heuristics. Experimental results show that the two methods perform well on some standard benchmarks.


Multiple antenna technologies

Abstract: Multiple antenna technologies have received high attention in the last few decades for their capabilities to improve the overall system performance. Multiple-input multiple-output systems include a variety of techniques capable of not only increase the reliability of the communication but also impressively boost the channel capacity. In addition, smart antenna systems can increase the link quality and lead to appreciable interference reduction.


Perfect Matchings in O(n \log n) Time in Regular Bipartite Graphs

Abstract: In this paper we consider the well-studied problem of finding a perfect matching in a d-regular bipartite graph on 2n nodes with m=nd edges. The best-known algorithm for general bipartite graphs (due to Hopcroft and Karp) takes time O(m\sqrt{n}). In regular bipartite graphs, however, a matching is known to be computable in O(m) time (due to Cole, Ost and Schirra). In a recent line of work by Goel, Kapralov and Khanna the O(m) time algorithm was improved first to \tilde O(min{m, n^{2.5}/d}) and then to \tilde O(min{m, n^2/d}). It was also shown that the latter algorithm is optimal up to polylogarithmic factors among all algorithms that use non-adaptive uniform sampling to reduce the size of the graph as a first step. In this paper, we give a randomized algorithm that finds a perfect matching in a d-regular graph and runs in O(n\log n) time (both in expectation and with high probability). The algorithm performs an appropriately truncated random walk on a modified graph to successively find augmenting paths. Our algorithm may be viewed as using adaptive uniform sampling, and is thus able to bypass the limitations of (non-adaptive) uniform sampling established in earlier work. We also show that randomization is crucial for obtaining o(nd) time algorithms by establishing an \Omega(nd) lower bound for any deterministic algorithm. Our techniques also give an algorithm that successively finds a matching in the support of a doubly stochastic matrix in expected time O(n\log^2 n) time, with O(m) pre-processing time; this gives a simple O(m+mn\log^2 n) time algorithm for finding the Birkhoff-von Neumann decomposition of a doubly stochastic matrix.


Capacity of Large-scale CSMA Wireless Networks

Abstract: In the literature, asymptotic studies of multi-hop wireless network capacity often consider only centralized and deterministic TDMA (time-division multi-access) coordination schemes. There have been fewer studies of the asymptotic capacity of large-scale wireless networks based on CSMA (carrier-sensing multi-access), which schedules transmissions in a distributed and random manner. With the rapid and widespread adoption of CSMA technology, a critical question is that whether CSMA networks can be as scalable as TDMA networks. To answer this question and explore the capacity of CSMA networks, we first formulate the models of CSMA protocols to take into account the unique CSMA characteristics not captured by existing interference models in the literature. These CSMA models determine the feasible states, and consequently the capacity of CSMA networks. We then study the throughput efficiency of CSMA scheduling as compared to TDMA. Finally, we tune the CSMA parameters so as to maximize the throughput to the optimal order. As a result, we show that CSMA can achieve throughput as $\Omega(\frac{1}{\sqrt{n}})$, the same order as optimal centralized TDMA, on uniform random networks. Our CSMA scheme makes use of an efficient backbone-peripheral routing scheme and a careful design of dual carrier-sensing and dual channel scheme. We also address the implementation issues of our CSMA scheme.


Comparing Single and Multiobjective Evolutionary Approaches to the Inventory and Transportation Problem

Abstract: EVITA, standing for Evolutionary Inventory and Transportation Algorithm, is a two-level methodology designed to address the Inventory and Transportation Problem (ITP) in retail chains. The top level uses an evolutionary algorithm to obtain delivery patterns for each shop on a weekly basis so as to minimise the inventory costs, while the bottom level solves the Vehicle Routing Problem (VRP) for every day in order to obtain the minimum transport costs associated to a particular set of patterns. The aim of this paper is to investigate whether a multiobjective approach to this problem can yield any advantage over the previously used single objective approach. The analysis performed allows us to conclude that this is not the case and that the single objective approach is in gene- ral preferable for the ITP in the case studied. A further conclusion is that it is useful to employ a classical algorithm such as Clarke & Wright's as the seed for other metaheuristics like local search or tabu search in order to provide good results for the Vehicle Routing Problem.


Three-dimensional conceptual model for service-oriented simulation

Abstract: In this letter, we propose a novel three-dimensional conceptual model for an emerging service-oriented simulation paradigm. The model can be used as a guideline or an analytic means to find the potential and possible future directions of the current simulation frameworks. In particular, the model inspects the crossover between the disciplines of modeling and simulation, service-orientation, and software/systems engineering. Finally, two specific simulation frameworks are studied as examples.


Digital Ecosystems

Abstract: We view Digital Ecosystems to be the digital counterparts of biological ecosystems, which are considered to be robust, self-organising and scalable architectures that can automatically solve complex, dynamic problems. So, this work is concerned with the creation, investigation, and optimisation of Digital Ecosystems, exploiting the self-organising properties of biological ecosystems. First, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. We then investigated its self-organising aspects, starting with an extension to the definition of Physical Complexity to include evolving agent populations. Next, we established stability of evolving agent populations over time, by extending the Chli-DeWilde definition of agent stability to include evolutionary dynamics. Further, we evaluated the diversity of the software agents within evolving agent populations. To conclude, we considered alternative augmentations to optimise and accelerate our Digital Ecosystem, by studying the accelerating effect of a clustering catalyst on the evolutionary dynamics. We also studied the optimising effect of targeted migration on the ecological dynamics, through the indirect and emergent optimisation of the agent migration patterns. Overall, we have advanced the understanding of creating Digital Ecosystems, the self-organisation that occurs within them, and the optimisation of their Ecosystem-Oriented Architecture.


Analyse en d\'ependances \`a l'aide des grammaires d'interaction

Abstract: This article proposes a method to extract dependency structures from phrase-structure level parsing with Interaction Grammars. Interaction Grammars are a formalism which expresses interactions among words using a polarity system. Syntactical composition is led by the saturation of polarities. Interactions take place between constituents, but as grammars are lexicalized, these interactions can be translated at the level of words. Dependency relations are extracted from the parsing process: every dependency is the consequence of a polarity saturation. The dependency relations we obtain can be seen as a refinement of the usual dependency tree. Generally speaking, this work sheds new light on links between phrase structure and dependency parsing.


Grouping Synonyms by Definitions

Abstract: We present a method for grouping the synonyms of a lemma according to its dictionary senses. The senses are defined by a large machine readable dictionary for French, the TLFi (Tr\'esor de la langue fran\c{c}aise informatis\'e) and the synonyms are given by 5 synonym dictionaries (also for French). To evaluate the proposed method, we manually constructed a gold standard where for each (word, definition) pair and given the set of synonyms defined for that word by the 5 synonym dictionaries, 4 lexicographers specified the set of synonyms they judge adequate. While inter-annotator agreement ranges on that task from 67% to at best 88% depending on the annotator pair and on the synonym dictionary being considered, the automatic procedure we propose scores a precision of 67% and a recall of 71%. The proposed method is compared with related work namely, word sense disambiguation, synonym lexicon acquisition and WordNet construction.


R\'esolution du "partition problem" par une approche arithm\'etique

Abstract: This article has been withdrawn


The Universal Recommender

Abstract: We describe the Universal Recommender, a recommender system for semantic datasets that generalizes domain-specific recommenders such as content-based, collaborative, social, bibliographic, lexicographic, hybrid and other recommenders. In contrast to existing recommender systems, the Universal Recommender applies to any dataset that allows a semantic representation. We describe the scalable three-stage architecture of the Universal Recommender and its application to Internet Protocol Television (IPTV). To achieve good recommendation accuracy, several novel machine learning and optimization problems are identified. We finally give a brief argument supporting the need for machine learning recommenders.


Planet-scale Human Mobility Measurement

Abstract: Research into, and design and construction of mobile systems and algorithms requires access to large-scale mobility data. Unfortunately, the wireless and mobile research community lacks such data. For instance, the largest available human contact traces contain only 100 nodes with very sparse connectivity, limited by experimental logistics. In this paper we pose a challenge to the community: how can we collect mobility data from billions of human participants? We re-assert the importance of large-scale datasets in communication network design, and claim that this could impact fundamental studies in other academic disciplines. In effect, we argue that planet-scale mobility measurements can help to save the world. For example, through understanding large-scale human mobility, we can track and model and contain the spread of epidemics of various kinds.


Securing Remote Procedure Calls over HTTPS

Abstract: Remote Procedure Calls (RPC) are widely used over the Internet as they provide a simple and elegant way of interaction between the client and the server. This paper proposes a solution for securing the remote procedure calls (RPC) by tunneling it through HTTPS (Hypertext Transfer Protocol over Secure Socket Layer). RPC over HTTP actually uses the Secure Socket Layer (SSL) protocol as a transport for the traffic. SSL mandates that the server authenticates itself to the client using a digital certificate (and associated private key). SSL is normally configured to encrypt traffic before transmitting it between the server and client and vice versa.


On Ordinal Covering of Proposals Using Balanced Incomplete Block Designs

Abstract: A frequently encountered problem in peer review systems is to facilitate pairwise comparisons of a given set of proposals by as few as referees as possible. In [8], it was shown that, if each referee is assigned to review k proposals then ceil{n(n-1)/k(k-1)} referees are necessary and ceil{n(2n-k)/k^2} referees are sufficient to cover all n(n-1)/2 pairs of n proposals. While the upper bound remains within a factor of 2 of the lower bound, it becomes relatively large for small values of k and the ratio of the upper bound to the lower bound is not less than 3/2 when 2 <= k <= n/2. In this paper, we show that, if sqrt(n) <= k <= n/2 then the upper and lower bounds can be made closer in that their ratio never exceeds 3/2. This is accomplished by a new method that assigns proposals to referees using a particular family of balanced incomplete block designs. Specifically, the new method uses ceil{n(n+k)/k^2} referees when n/k is a prime power, n divides k^2, and sqrt(n) <= k <= n/2. Comparing this new upper bound to the one given in [8] shows that the new upper bound approaches the lower bound as k tends to sqrt(n) whereas the upper bound in [8] approaches the lower bound as k tends to n. Therefore, the new method given here when combined together with the one in [8] provides an assignment whose upper bound referee complexity always remains within a factor of 3/2 of the lower bound when sqrt(n) <= k <= n, thereby improving upon the assignment described in [8]. Furthermore, the new method provides a minimal covering, i.e., it uses the minimum number of referees possible when k = sqrt(n) and k is a prime power.


Robustness of the Digital Image Watermarking Techniques against Brightness and Rotation Attack

Abstract: The recent advent in the field of multimedia proposed a many facilities in transport, transmission and manipulation of data. Along with this advancement of facilities there are larger threats in authentication of data, its licensed use and protection against illegal use of data. A lot of digital image watermarking techniques have been designed and implemented to stop the illegal use of the digital multimedia images. This paper compares the robustness of three different watermarking schemes against brightness and rotation attacks. The robustness of the watermarked images has been verified on the parameters of PSNR (Peak Signal to Noise Ratio), RMSE (Root Mean Square Error) and MAE (Mean Absolute Error).


Route Distribution Incentives

Abstract: We present an incentive model for route distribution in the context of path vector routing protocols and we focus on the Border Gateway Protocol (BGP). BGP is the de-facto protocol for interdomain routing on the Internet. We model BGP route distribution and computation using a game in which a BGP speaker advertises its prefix to its direct neighbors promising them a reward for further distributing the route deeper into the network, the neighbors do the same thing with their neighbors, and so on. The result of this cascaded route distribution is an advertised prefix and hence reachability of the BGP speaker. We first study the convergence of BGP protocol dynamics to a unique outcome tree in the defined game. We then proceed to study the existence of equilibria in the full information game considering competition dynamics. We focus our work on the simplest two classes of graphs: 1) the line (and the tree) graphs which involve no competition, and 2) the ring graph which involves competition.


ODMRP with Quality of Service and local recovery with security Support

Abstract: In this paper we focus on one critical issue in mobile ad hoc networks that is multicast routing and propose a mesh based on demand multicast routing protocol for Ad-Hoc networks with QoS (quality of service) support. Then a model was presented which is used for create a local recovering mechanism in order to joining the nodes to multi sectional groups at the minimized time and method for security in this protocol we present .


Mathematics, Recursion, and Universals in Human Languages

Abstract: There are many scientific problems generated by the multiple and conflicting alternative definitions of linguistic recursion and human recursive processing that exist in the literature. The purpose of this article is to make available to the linguistic community the standard mathematical definition of recursion and to apply it to discuss linguistic recursion. As a byproduct, we obtain an insight into certain "soft universals" of human languages, which are related to cognitive constructs necessary to implement mathematical reasoning, i.e. mathematical model theory.


Exploiting Unlabeled Data to Enhance Ensemble Diversity

Abstract: Ensemble learning aims to improve generalization ability by using multiple base learners. It is well-known that to construct a good ensemble, the base learners should be accurate as well as diverse. In this paper, unlabeled data is exploited to facilitate ensemble learning by helping augment the diversity among the base learners. Specifically, a semi-supervised ensemble method named UDEED is proposed. Unlike existing semi-supervised ensemble methods where error-prone pseudo-labels are estimated for unlabeled data to enlarge the labeled data to improve accuracy, UDEED works by maximizing accuracies of base learners on labeled data while maximizing diversity among them on unlabeled data. Experiments show that UDEED can effectively utilize unlabeled data for ensemble learning and is highly competitive to well-established semi-supervised ensemble methods.


Extension of Path Probability Method to Approximate Inference over Time

Abstract: There has been a tremendous growth in publicly available digital video footage over the past decade. This has necessitated the development of new techniques in computer vision geared towards efficient analysis, storage and retrieval of such data. Many mid-level computer vision tasks such as segmentation, object detection, tracking, etc. involve an inference problem based on the video data available. Video data has a high degree of spatial and temporal coherence. The property must be intelligently leveraged in order to obtain better results. Graphical models, such as Markov Random Fields, have emerged as a powerful tool for such inference problems. They are naturally suited for expressing the spatial dependencies present in video data, It is however, not clear, how to extend the existing techniques for the problem of inference over time. This thesis explores the Path Probability Method, a variational technique in statistical mechanics, in the context of graphical models and approximate inference problems. It extends the method to a general framework for problems involving inference in time, resulting in an algorithm, \emph{DynBP}. We explore the relation of the algorithm with existing techniques, and find the algorithm competitive with existing approaches. The main contribution of this thesis are the extended GBP algorithm, the extension of Path Probability Methods to the DynBP algorithm and the relationship between them. We have also explored some applications in computer vision involving temporal evolution with promising results.


Randomized Algorithms for Large scale SVMs

Abstract: We propose a randomized algorithm for training Support vector machines(SVMs) on large datasets. By using ideas from Random projections we show that the combinatorial dimension of SVMs is $O({log} n)$ with high probability. This estimate of combinatorial dimension is used to derive an iterative algorithm, called RandSVM, which at each step calls an existing solver to train SVMs on a randomly chosen subset of size $O({log} n)$. The algorithm has probabilistic guarantees and is capable of training SVMs with Kernels for both classification and regression problems. Experiments done on synthetic and real life data sets demonstrate that the algorithm scales up existing SVM learners, without loss of accuracy.


Packet Scheduling in a Size-Bounded Buffer

Abstract: We consider algorithms to schedule packets with values and deadlines in a size-bounded buffer. At any time, the buffer can store at most B packets. Packets arrive over time. Each packet has a non-negative value and an integer deadline. In each time step, at most one packet can be sent. Packets can be dropped at any time before they are sent. The objective is to maximize the total value gained by delivering packets no later than their respective deadlines. This model generalizes the well-studied bounded-delay model (Hajek. CISS 2001. Kesselman et al. STOC 2001). We first provide an optimal offline algorithm for this model. Then we present an alternative proof of the 2-competitive deterministic online algorithm (Fung. arXiv July 2009). We also prove that the lower bound of competitive ratio of a family of (deterministic and randomized) algorithms is 2 - 1 / B.


Harvesting SSL Certificate Data to Identify Web-Fraud

Abstract: Web-fraud is one of the most unpleasant features of today's Internet. Two well-known examples of fraudulent activities on the web are phishing and typosquatting. Their effects range from relatively benign (such as unwanted ads) to downright sinister (especially, when typosquatting is combined with phishing). This paper presents a novel technique to detect web-fraud domains that utilize HTTPS. To this end, we conduct the first comprehensive study of SSL certificates. We analyze certificates of legitimate and popular domains and those used by fraudulent ones. Drawing from extensive measurements, we build a classifier that detects such malicious domains with high accuracy.


Efficient and Error-Correcting Data Structures for Membership and Polynomial Evaluation

Abstract: We construct efficient data structures that are resilient against a constant fraction of adversarial noise. Our model requires that the decoder answers most queries correctly with high probability and for the remaining queries, the decoder with high probability either answers correctly or declares "don't know." Furthermore, if there is no noise on the data structure, it answers all queries correctly with high probability. Our model is the common generalization of a model proposed recently by de Wolf and the notion of "relaxed locally decodable codes" developed in the PCP literature. We measure the efficiency of a data structure in terms of its length, measured by the number of bits in its representation, and query-answering time, measured by the number of bit-probes to the (possibly corrupted) representation. In this work, we study two data structure problems: membership and polynomial evaluation. We show that these two problems have constructions that are simultaneously efficient and error-correcting.


Analytical Models for Energy Consumption in Infrastructure WLAN STAs Carrying TCP Traffic

Abstract: We develop analytical models for estimating the energy spent by stations (STAs) in infrastructure WLANs when performing TCP controlled file downloads. We focus on the energy spent in radio communication when the STAs are in the Continuously Active Mode (CAM), or in the static Power Save Mode (PSM). Our approach is to develop accurate models for obtaining the fraction of times the STA radios spend in idling, receiving and transmitting. We discuss two traffic models for each mode of operation: (i) each STA performs one large file download, and (ii) the STAs perform short file transfers. We evaluate the rate of STA energy expenditure with long file downloads, and show that static PSM is worse than just using CAM. For short file downloads we compute the number of file downloads that can be completed with given battery capacity, and show that PSM performs better than CAM for this case. We provide a validation of our analytical models using the NS-2 simulator. In contrast to earlier work on analytical modeling of PSM, our models that capture the details of the interactions between the 802.11 MAC in PSM and certain aspects of TCP.


Kinematic calibration of Orthoglide-type mechanisms from observation of parallel leg motions

Abstract: The paper proposes a new calibration method for parallel manipulators that allows efficient identification of the joint offsets using observations of the manipulator leg parallelism with respect to the base surface. The method employs a simple and low-cost measuring system, which evaluates deviation of the leg location during motions that are assumed to preserve the leg parallelism for the nominal values of the manipulator parameters. Using the measured deviations, the developed algorithm estimates the joint offsets that are treated as the most essential parameters to be identified. The validity of the proposed calibration method and efficiency of the developed numerical algorithms are confirmed by experimental results. The sensitivity of the measurement methods and the calibration accuracy are also studied.


Approximating the minimum length of synchronizing words is hard

Abstract: We prove that, unless $\mathrm{P}=\mathrm{NP}$, no polynomial algorithm can approximate the minimum length of \sws for a given \san within a constant factor.


On Carpi and Alessandro conjecture

Abstract: The well known open \v{C}ern\'y conjecture states that each \san with $n$ states has a \sw of length at most $(n-1)^2$. On the other hand, the best known upper bound is cubic of $n$. Recently, in the paper \cite{CARPI1} of Alessandro and Carpi, the authors introduced the new notion of strongly transitivity for automata and conjectured that this property with a help of \emph{Extension} method allows to get a quadratic upper bound for the length of the shortest \sws. They also confirmed this conjecture for circular automata. We disprove this conjecture and the long-standing \emph{Extension} conjecture too. We also consider the widely used Extension method and its perspectives.


Method of resolution of 3SAT in polynomial time

Abstract: Presentation of a Method for determining whether a problem 3Sat has solution, and if yes to find one, in time max O(n^15). Is thus proved that the problem 3Sat is fully resolved in polynomial time and therefore that it is in P, by the work of Cook and Levin, and can transform a SAT problem in a 3Sat in polynomial time (ref. Karp), it follows that P = NP. Open Source program is available at http://www.visainformatica.it/3sat


A note on the hardness of graph diameter augmentation problems

Abstract: A graph has \emph{diameter} D if every pair of vertices are connected by a path of at most D edges. The Diameter-D Augmentation problem asks how to add the a number of edges to a graph in order to make the resulting graph have diameter D. It was previously known that this problem is NP-hard \cite{GJ}, even in the D=2 case. In this note, we give a simpler reduction to arrive at this fact and show that this problem is W[2]-hard.


A Method for Extraction and Recognition of Isolated License Plate Characters

Abstract: A method to extract and recognize isolated characters in license plates is proposed. In extraction stage, the proposed method detects isolated characters by using Difference-of-Gaussian (DOG) function, The DOG function, similar to Laplacian of Gaussian function, was proven to produce the most stable image features compared to a range of other possible image functions. The candidate characters are extracted by doing connected component analysis on different scale DOG images. In recognition stage, a novel feature vector named accumulated gradient projection vector (AGPV) is used to compare the candidate character with the standard ones. The AGPV is calculated by first projecting pixels of similar gradient orientations onto specific axes, and then accumulates the projected gradient magnitudes by each axis. In the experiments, the AGPVs are proven to be invariant from image scaling and rotation, and robust to noise and illumination change.


Stiffness Analysis Of Multi-Chain Parallel Robotic Systems

Abstract: The paper presents a new stiffness modelling method for multi-chain parallel robotic manipulators with flexible links and compliant actuating joints. In contrast to other works, the method involves a FEA-based link stiffness evaluation and employs a new solution strategy of the kinetostatic equations, which allows computing the stiffness matrix for singular postures and to take into account influence of the external forces. The advantages of the developed technique are confirmed by application examples, which deal with stiffness analysis of a parallel manipulator of the Orthoglide family


Rossler Nonlinear Dynamical Machine for Cryptography Applications

Abstract: In many of the cryptography applications like password or IP address encryption schemes, symmetric cryptography is useful. In these relatively simpler applications of cryptography, asymmetric cryptography is difficult to justify on account of the computational and implementation complexities associated with asymmetric cryptography. Symmetric schemes make use of a single shared key known only between the two communicating hosts. This shared key is used both for the encryption as well as the decryption of data. This key has to be small in size besides being a subset of a potentially large keyspace making it convenient for the communicating hosts while at the same time making cryptanalysis difficult for the potential attackers. In the present work, an abstract Rossler nonlinear dynamical machine has been described first. The Rossler system exhibits chaotic dynamics for certain values of system parameters and initial conditions. The chaotic dynamics of the Rossler system with its apparently erratic and irregular characteristics and extreme sensitivity to the initial conditions has been used for the design of the cryptographic key in an attempt to increase the confusion and the challenge for the potential attackers.


Periodicity in tilings

Abstract: Tilings and tiling systems are an abstract concept that arise both as a computational model and as a dynamical system. In this paper, we characterize the sets of periods that a tiling system can produce. We prove that up to a slight recoding, they correspond exactly to languages in the complexity classes $\nspace{n}$ and $\cne$.


Large-girth roots of graphs

Abstract: We study the problem of recognizing graph powers and computing roots of graphs. We provide a polynomial time recognition algorithm for r-th powers of graphs of girth at least 2r+3, thus improving a bound conjectured by Farzad et al. (STACS 2009). Our algorithm also finds all r-th roots of a given graph that have girth at least 2r+3 and no degree one vertices, which is a step towards a recent conjecture of Levenshtein that such root should be unique. On the negative side, we prove that recognition becomes an NP-complete problem when the bound on girth is about twice smaller. Similar results have so far only been attempted for r=2,3.


Automatic modular abstractions for template numerical constraints

Abstract: We propose a method for automatically generating abstract transformers for static analysis by abstract interpretation. The method focuses on linear constraints on programs operating on rational, real or floating-point variables and containing linear assignments and tests. In addition to loop-free code, the same method also applies for obtaining least fixed points as functions of the precondition, which permits the analysis of loops and recursive functions. Our algorithms are based on new quantifier elimination and symbolic manipulation techniques. Given the specification of an abstract domain, and a program block, our method automatically outputs an implementation of the corresponding abstract transformer. It is thus a form of program transformation. The motivation of our work is data-flow synchronous programming languages, used for building control-command embedded systems, but it also applies to imperative and functional programming.


Beyond O*(2^n) in domination-type problems

Abstract: In this paper we provide algorithms faster than O*(2^n) for several NP-complete domination-type problems. More precisely, we provide: an algorithm for CAPACITATED DOMINATING SET that solves it in O(1.89^n), a branch-and-reduce algorithm solving LARGEST IRREDUNDANT SET in O(1.9657^n) time and a simple iterative-DFS algorithm for SMALLEST INCLUSION-MAXIMAL IRREDUNDANT SET that solves it in O(1.999956^n) time. We also provide an exponential approximation scheme for CAPACITATED DOMINATING SET. All algorithms require polynomial space. Despite the fact that the discussed problems are quite similar to the DOMINATING SET problem, we are not aware of any published algorithms solving these problems faster than the obvious O*(2^n) solution prior to this paper.


Long non-crossing configurations in the plane

Abstract: We revisit several maximization problems for geometric networks design under the non-crossing constraint, first studied by Alon, Rajagopalan and Suri (ACM Symposium on Computational Geometry, 1993). Given a set of $n$ points in the plane in general position (no three points collinear), compute a longest non-crossing configuration composed of straight line segments that is: (a) a matching (b) a Hamiltonian path (c) a spanning tree. Here we obtain new results for (b) and (c), as well as for the Hamiltonian cycle problem: (i) For the longest non-crossing Hamiltonian path problem, we give an approximation algorithm with ratio $\frac{2}{\pi+1} \approx 0.4829$. The previous best ratio, due to Alon et al., was $1/\pi \approx 0.3183$. Moreover, the ratio of our algorithm is close to $2/\pi$ on a relatively broad class of instances: for point sets whose perimeter (or diameter) is much shorter than the maximum length matching. The algorithm runs in $O(n^{7/3}\log{n})$ time. (ii) For the longest non-crossing spanning tree problem, we give an approximation algorithm with ratio 0.502 which runs in $O(n \log{n})$ time. The previous ratio, 1/2, due to Alon et al., was achieved by a quadratic time algorithm. Along the way, we first re-derive the result of Alon et al. with a faster $O(n \log{n})$-time algorithm and a very simple analysis. (iii) For the longest non-crossing Hamiltonian cycle problem, we give an approximation algorithm whose ratio is close to $2/\pi$ on a relatively broad class of instances: for point sets with the product $\bf{<}$diameter$\times$ convex hull size $\bf{>}$ much smaller than the maximum length matching. The algorithm runs in $O(n^{7/3}\log{n})$ time. No previous approximation results were known for this problem.


A Numerical Algorithm for Zero Counting. II: Distance to Ill-posedness and Smoothed Analysis

Abstract: We show a Condition Number Theorem for the condition number of zero counting for real polynomial systems. That is, we show that this condition number equals the inverse of the normalized distance to the set of ill-posed systems (i.e., those having multiple real zeros). As a consequence, a smoothed analysis of this condition number follows.


Personal Information Databases

Abstract: One of the most important aspects of security organization is to establish a framework to identify security significant points where policies and procedures are declared. The (information) security infrastructure comprises entities, processes, and technology. All are participants in handling information, which is the item that needs to be protected. Privacy and security information technology is a critical and unmet need in the management of personal information. This paper proposes concepts and technologies for management of personal information. Two different types of information can be distinguished: personal information and nonpersonal information. Personal information can be either personal identifiable information (PII), or nonidentifiable information (NII). Security, policy, and technical requirements can be based on this distinction. At the conceptual level, PII is defined and formalized by propositions over infons (discrete pieces of information) that specify transformations in PII and NII. PII is categorized into simple infons that reflect the proprietor s aspects, relationships with objects, and relationships with other proprietors. The proprietor is the identified person about whom the information is communicated. The paper proposes a database organization that focuses on the PII spheres of proprietors. At the design level, the paper describes databases of personal identifiable information built exclusively for this type of information, with their own conceptual scheme, system management, and physical structure.


Improving Effectiveness Of ELearning In Maintenance Using Interactive 3D

Abstract: In aerospace and defense, training is being carried out on the web by viewing PowerPoint presentations, manuals and videos that are limited in their ability to convey information to the technician. Interactive training in the form of 3D is a more cost effective approach compared to creation of physical simulations and mockups. This paper demonstrates how training using interactive 3D simulations in elearning achieves a reduction in the time spent in training and improves the efficiency of a trainee performing the installation or removal.


Breaking the 2^n-Barrier for Irredundance: A Parameterized Route to Solving Exact Puzzles

Abstract: The lower and the upper irredundance numbers of a graph $G$, denoted $ir(G)$ and $IR(G)$ respectively, are conceptually linked to domination and independence numbers and have numerous relations to other graph parameters. It is a long-standing open question whether determining these numbers for a graph $G$ on $n$ vertices admits exact algorithms running in time less than the trivial $\Omega(2^n)$ enumeration barrier. We solve these open problems by devising parameterized algorithms for the dual of the natural parameterizations of the problems with running times faster than $O^*(4^{k})$. For example, we present an algorithm running in time $O^*(3.069^{k})$ for determining whether $IR(G)$ is at least $n-k$. Although the corresponding problem has been known to be in FPT by kernelization techniques, this paper offers the first parameterized algorithms with an exponential dependency on the parameter in the running time. Additionally, our work also appears to be the first example of a parameterized approach leading to a solution to a problem in exponential time algorithmics where the natural interpretation as an exact exponential-time algorithm fails.


An Empirical Comparative Study of Checklist based and Ad Hoc Code Reading Techniques in a Distributed Groupware Environment

Abstract: Software inspection is a necessary and important tool for software quality assurance. Since it was introduced by Fagan at IBM in 1976, arguments exist as to which method should be adopted to carry out the exercise, whether it should be paper based or tool based, and what reading technique should be used on the inspection document. Extensive works have been done to determine the effectiveness of reviewers in paper based environment when using ad hoc and checklist reading techniques. In this work, we take the software inspection research further by examining whether there is going to be any significant difference in defect detection effectiveness of reviewers when they use either ad hoc or checklist reading techniques in a distributed groupware environment. Twenty final year undergraduate students of computer science, divided into ad hoc and checklist reviewers groups of ten members each were employed to inspect a medium sized java code synchronously on groupware deployed on the Internet. The data obtained were subjected to tests of hypotheses using independent T test and correlation coefficients. Results from the study indicate that there are no significant differences in the defect detection effectiveness, effort in terms of time taken in minutes and false positives reported by the reviewers using either ad hoc or checklist based reading techniques in the distributed groupware environment studied.


A Measure of the Connection Strengths between Graph Vertices with Applications

Abstract: We present a simple iterative strategy for measuring the connection strength between a pair of vertices in a graph. The method is attractive in that it has a linear complexity and can be easily parallelized. Based on an analysis of the convergence property, we propose a mutually reinforcing model to explain the intuition behind the strategy. The practical effectiveness of this measure is demonstrated through several combinatorial optimization problems on graphs and hypergraphs.


Towards Multimodal Content Representation

Abstract: Multimodal interfaces, combining the use of speech, graphics, gestures, and facial expressions in input and output, promise to provide new possibilities to deal with information in more effective and efficient ways, supporting for instance: - the understanding of possibly imprecise, partial or ambiguous multimodal input; - the generation of coordinated, cohesive, and coherent multimodal presentations; - the management of multimodal interaction (e.g., task completion, adapting the interface, error prevention) by representing and exploiting models of the user, the domain, the task, the interactive context, and the media (e.g. text, audio, video). The present document is intended to support the discussion on multimodal content representation, its possible objectives and basic constraints, and how the definition of a generic representation framework for multimodal content representation may be approached. It takes into account the results of the Dagstuhl workshop, in particular those of the informal working group on multimodal meaning representation that was active during the workshop (see http://www.dfki.de/~wahlster/Dagstuhl_Multi_Modality, Working Group 4).


Higher-dimensional models of networks

Abstract: Networks are often studied as graphs, where the vertices stand for entities in the world and the edges stand for connections between them. While relatively easy to study, graphs are often inadequate for modeling real-world situations, especially those that include contexts of more than two entities. For these situations, one typically uses hypergraphs or simplicial complexes. In this paper, we provide a precise framework in which graphs, hypergraphs, simplicial complexes, and many other categories, all of which model higher graphs, can be studied side-by-side. We show how to transform a hypergraph into its nearest simplicial analogue, for example. Our framework includes many new categories as well, such as one that models broadcasting networks. We give several examples and applications of these ideas.


Lightweight Data Indexing and Compression in External Memory

Abstract: In this paper we describe algorithms for computing the BWT and for building (compressed) indexes in external memory. The innovative feature of our algorithms is that they are lightweight in the sense that, for an input of size $n$, they use only ${n}$ bits of disk working space while all previous approaches use $\Th{n \log n}$ bits of disk working space. Moreover, our algorithms access disk data only via sequential scans, thus they take full advantage of modern disk features that make sequential disk accesses much faster than random accesses. We also present a scan-based algorithm for inverting the BWT that uses $\Th{n}$ bits of working space, and a lightweight {\em internal-memory} algorithm for computing the BWT which is the fastest in the literature when the available working space is $\os{n}$ bits. Finally, we prove {\em lower} bounds on the complexity of computing and inverting the BWT via sequential scans in terms of the classic product: internal-memory space $\times$ number of passes over the disk data.


Dependent Randomized Rounding for Matroid Polytopes and Applications

Abstract: Motivated by several applications, we consider the problem of randomly rounding a fractional solution in a matroid (base) polytope to an integral one. We consider the pipage rounding technique and also present a new technique, randomized swap rounding. Our main technical results are concentration bounds for functions of random variables arising from these rounding techniques. We prove Chernoff-type concentration bounds for linear functions of random variables arising from both techniques, and also a lower-tail exponential bound for monotone submodular functions of variables arising from randomized swap rounding. The following are examples of our applications: (1) We give a (1-1/e-epsilon)-approximation algorithm for the problem of maximizing a monotone submodular function subject to 1 matroid and k linear constraints, for any constant k and epsilon>0. (2) We present a result on minimax packing problems that involve a matroid base constraint. We give an O(log m / log log m)-approximation for the general problem Min {lambda: x \in {0,1}^N, x \in B(M), Ax <= lambda b}, where m is the number of packing constraints. (3) We generalize the continuous greedy algorithm to problems involving multiple submodular functions, and use it to find a (1-1/e-epsilon)-approximate pareto set for the problem of maximizing a constant number of monotone submodular functions subject to a matroid constraint. An example is the Submodular Welfare Problem where we are looking for an approximate pareto set with respect to individual players' utilities.


A Strategy for Maker in the Clique Game which Helps to Tackle some Open Problems by Beck

Abstract: We study Maker/Breaker games on the edges of the complete graph, as introduced by Chvatal and Erdos. We show that in the (m:b) clique game played on K_{N}, the complete graph on N vertices, Maker can achieve a K_{q} for q = (m/(log_{2}(b + 1)) - o(1)) * log N, which partially solves an open problem by Beck. Moreover, we show that in the (1:1) clique game played on K_{N} for a sufficiently large N, Maker can achieve a K_{q} in only 2^(2q/3) moves, which improves the previous best bound and answers a question of Beck. Finally we consider the so called tournament game. A tournament is a directed graph where every pair of vertices is connected by a single directed edge. The tournament game is played on K_{N}. At the beginning Breaker fixes an arbitrary tournament T_{q} on q vertices. Maker and Breaker then alternately take turns at claiming one unclaimed edge e and selecting one of the two possible orientations. Maker wins if his graph contains a copy of the goal tournament T_{q}; otherwise Breaker wins. We show that Maker wins the tournament game on K_{N} with q = (1 - o(1))*log_{2}(N) which supports the random graph intuition: the threshold for q is asymptotically the same for the game played by two "clever'' players and the game played by two ``random'' players. This last result solves an open problem of Beck which he included in his list of the seven most humiliating open problems.


Exploration of Periodically Varying Graphs

Abstract: We study the computability and complexity of the exploration problem in a class of highly dynamic graphs: periodically varying (PV) graphs, where the edges exist only at some (unknown) times defined by the periodic movements of carriers. These graphs naturally model highly dynamic infrastructure-less networks such as public transports with fixed timetables, low earth orbiting (LEO) satellite systems, security guards' tours, etc. We establish necessary conditions for the problem to be solved. We also derive lower bounds on the amount of time required in general, as well as for the PV graphs defined by restricted classes of carriers movements: simple routes, and circular routes. We then prove that the limitations on computability and complexity we have established are indeed tight. In fact we prove that all necessary conditions are also sufficient and all lower bounds on costs are tight. We do so constructively presenting two worst case optimal solution algorithms, one for anonymous systems, and one for those with distinct nodes ids. An added benefit is that the algorithms are rather simple.


Clustering with Obstacles in Spatial Databases

Abstract: Clustering large spatial databases is an important problem, which tries to find the densely populated regions in a spatial area to be used in data mining, knowledge discovery, or efficient information retrieval. However most algorithms have ignored the fact that physical obstacles such as rivers, lakes, and highways exist in the real world and could thus affect the result of the clustering. In this paper, we propose CPO, an efficient clustering technique to solve the problem of clustering in the presence of obstacles. The proposed algorithm divides the spatial area into rectangular cells. Each cell is associated with statistical information used to label the cell as dense or non-dense. It also labels each cell as obstructed (i.e. intersects any obstacle) or nonobstructed. For each obstructed cell, the algorithm finds a number of non-obstructed sub-cells. Then it finds the dense regions of non-obstructed cells or sub-cells by a breadthfirst search as the required clusters with a center to each region.


Algorithm for Spatial Clustering with Obstacles

Abstract: In this paper, we propose an efficient clustering technique to solve the problem of clustering in the presence of obstacles. The proposed algorithm divides the spatial area into rectangular cells. Each cell is associated with statistical information that enables us to label the cell as dense or non-dense. We also label each cell as obstructed (i.e. intersects any obstacle) or non-obstructed. Then the algorithm finds the regions (clusters) of connected, dense, non-obstructed cells. Finally, the algorithm finds a center for each such region and returns those centers as centers of the relatively dense regions (clusters) in the spatial area.


A baseline for content-based blog classification

Abstract: A content-based network representation of web logs (blogs) using a basic word-overlap similarity measure is presented. Due to a strong signal in blog data the approach is sufficient for accurately classifying blogs. Using Swedish blog data we demonstrate that blogs that treat similar subjects are organized in clusters that, in turn, are hierarchically organized in higher-order clusters. The simplicity of the representation renders it both computationally tractable and transparent. We therefore argue that the approach is suitable as a baseline when developing and analyzing more advanced content-based representations of the blogosphere.


Manipulation and gender neutrality in stable marriage procedures

Abstract: The stable marriage problem is a well-known problem of matching men to women so that no man and woman who are not married to each other both prefer each other. Such a problem has a wide variety of practical applications ranging from matching resident doctors to hospitals to matching students to schools. A well-known algorithm to solve this problem is the Gale-Shapley algorithm, which runs in polynomial time. It has been proven that stable marriage procedures can always be manipulated. Whilst the Gale-Shapley algorithm is computationally easy to manipulate, we prove that there exist stable marriage procedures which are NP-hard to manipulate. We also consider the relationship between voting theory and stable marriage procedures, showing that voting rules which are NP-hard to manipulate can be used to define stable marriage procedures which are themselves NP-hard to manipulate. Finally, we consider the issue that stable marriage procedures like Gale-Shapley favour one gender over the other, and we show how to use voting rules to make any stable marriage procedure gender neutral.


Dealing with incomplete agents' preferences and an uncertain agenda in group decision making via sequential majority voting

Abstract: We consider multi-agent systems where agents' preferences are aggregated via sequential majority voting: each decision is taken by performing a sequence of pairwise comparisons where each comparison is a weighted majority vote among the agents. Incompleteness in the agents' preferences is common in many real-life settings due to privacy issues or an ongoing elicitation process. In addition, there may be uncertainty about how the preferences are aggregated. For example, the agenda (a tree whose leaves are labelled with the decisions being compared) may not yet be known or fixed. We therefore study how to determine collectively optimal decisions (also called winners) when preferences may be incomplete, and when the agenda may be uncertain. We show that it is computationally easy to determine if a candidate decision always wins, or may win, whatever the agenda. On the other hand, it is computationally hard to know wheth er a candidate decision wins in at least one agenda for at least one completion of the agents' preferences. These results hold even if the agenda must be balanced so that each candidate decision faces the same number of majority votes. Such results are useful for reasoning about preference elicitation. They help understand the complexity of tasks such as determining if a decision can be taken collectively, as well as knowing if the winner can be manipulated by appropriately ordering the agenda.


Elicitation strategies for fuzzy constraint problems with missing preferences: algorithms and experimental studies

Abstract: Fuzzy constraints are a popular approach to handle preferences and over-constrained problems in scenarios where one needs to be cautious, such as in medical or space applications. We consider here fuzzy constraint problems where some of the preferences may be missing. This models, for example, settings where agents are distributed and have privacy issues, or where there is an ongoing preference elicitation process. In this setting, we study how to find a solution which is optimal irrespective of the missing preferences. In the process of finding such a solution, we may elicit preferences from the user if necessary. However, our goal is to ask the user as little as possible. We define a combined solving and preference elicitation scheme with a large number of different instantiations, each corresponding to a concrete algorithm which we compare experimentally. We compute both the number of elicited preferences and the "user effort", which may be larger, as it contains all the preference values the user has to compute to be able to respond to the elicitation requests. While the number of elicited preferences is important when the concern is to communicate as little information as possible, the user effort measures also the hidden work the user has to do to be able to communicate the elicited preferences. Our experimental results show that some of our algorithms are very good at finding a necessarily optimal solution while asking the user for only a very small fraction of the missing preferences. The user effort is also very small for the best algorithms. Finally, we test these algorithms on hard constraint problems with possibly missing constraints, where the aim is to find feasible solutions irrespective of the missing constraints.


Flow-Based Propagators for the SEQUENCE and Related Global Constraints

Abstract: We propose new filtering algorithms for the SEQUENCE constraint and some extensions of the SEQUENCE constraint based on network flows. We enforce domain consistency on the SEQUENCE constraint in $O(n^2)$ time down a branch of the search tree. This improves upon the best existing domain consistency algorithm by a factor of $O(\log n)$. The flows used in these algorithms are derived from a linear program. Some of them differ from the flows used to propagate global constraints like GCC since the domains of the variables are encoded as costs on the edges rather than capacities. Such flows are efficient for maintaining bounds consistency over large domains and may be useful for other global constraints.


The Weighted CFG Constraint

Abstract: We introduce the weighted CFG constraint and propose a propagation algorithm that enforces domain consistency in $O(n^3|G|)$ time. We show that this algorithm can be decomposed into a set of primitive arithmetic constraints without hindering propagation.


SQL/JavaScript Hybrid Worms As Two-stage Quines

Abstract: Delving into present trends and anticipating future malware trends, a hybrid, SQL on the server-side, JavaScript on the client-side, self-replicating worm based on two-stage quines was designed and implemented on an ad-hoc scenario instantiating a very common software pattern. The proof of concept code combines techniques seen in the wild, in the form of SQL injections leading to cross-site scripting JavaScript inclusion, and seen in the laboratory, in the form of SQL quines propa- gated via RFIDs, resulting in a hybrid code injection. General features of hybrid worms are also discussed.


Envy, Multi Envy, and Revenue Maximization

Abstract: We study the envy free pricing problem faced by a seller who wishes to maximize revenue by setting prices for bundles of items. If there is an unlimited supply of items and agents are single minded then we show that finding the revenue maximizing envy free allocation/pricing can be solved in polynomial time by reducing it to an instance of weighted independent set on a perfect graph. We define an allocation/pricing as \textit{multi envy free} if no agent wishes to replace her allocation with the union of the allocations of some set of other agents and her price with the sum of their prices. We show that it is \textit{coNP}-hard to decide if a given allocation/pricing is multi envy free. We also show that revenue maximization multi envy free allocation/pricing is \textit{APX} hard. Furthermore, we give efficient algorithms and hardness results for various variants of the highway problem.


Scalable Inference for Latent Dirichlet Allocation

Abstract: We investigate the problem of learning a topic model - the well-known Latent Dirichlet Allocation - in a distributed manner, using a cluster of C processors and dividing the corpus to be learned equally among them. We propose a simple approximated method that can be tuned, trading speed for accuracy according to the task at hand. Our approach is asynchronous, and therefore suitable for clusters of heterogenous machines.


A note on the sign degree of formulas

Abstract: Recent breakthroughs in quantum query complexity have shown that any formula of size n can be evaluated with O(sqrt(n)log(n)/log log(n)) many quantum queries in the bounded-error setting [FGG08, ACRSZ07, RS08b, Rei09]. In particular, this gives an upper bound on the approximate polynomial degree of formulas of the same magnitude, as approximate polynomial degree is a lower bound on quantum query complexity [BBCMW01]. These results essentially answer in the affirmative a conjecture of O'Donnell and Servedio [O'DS03] that the sign degree--the minimal degree of a polynomial that agrees in sign with a function on the Boolean cube--of every formula of size n is O(sqrt(n)). In this note, we show that sign degree is super-multiplicative under function composition. Combining this result with the above mentioned upper bounds on the quantum query complexity of formulas allows the removal of logarithmic factors to show that the sign degree of every size n formula is at most sqrt(n).