OpenRaiser/Intern-Atlas huggingface dataset:
PAC Learning Mixtures of Axis-Aligned Gaussians with No Separation Assumption
Venue: arXiv cs.LG 2006
Year: 2006

We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kearns et al. Here the task is to construct a hypothesis mixture of Gaussians that is statistically indistinguishable from the actual mixture generating the data; specifically, the KL-divergence should be at most epsilon. In this scenario, we give a poly(n/epsilon)-time algorithm that learns the class of mixtures of any constant number of axis-aligned Gaussians in n-dimensional Euclidean space. Our algorithm makes no assumptions about the separation between the means of the Gaussians, nor does it have any dependence on the minimum mixing weight. This is in contrast to learning results known in the ``clustering'' model, where such assumptions are unavoidable. Our algorithm relies on the method of moments, and a subalgorithm developed in previous work by the authors (FOCS 2005) for a discrete mixture-learning problem.
Traveing Salesperson Problems for a double integrator
Venue: arXiv cs.RO 2006
Year: 2006

In this paper we propose some novel path planning strategies for a double integrator with bounded velocity and bounded control inputs. First, we study the following version of the Traveling Salesperson Problem (TSP): given a set of points in $\real^d$, find the fastest tour over the point set for a double integrator. We first give asymptotic bounds on the time taken to complete such a tour in the worst-case. Then, we study a stochastic version of the TSP for double integrator where the points are randomly sampled from a uniform distribution in a compact environment in $\real^2$ and $\real^3$. We propose novel algorithms that perform within a constant factor of the optimal strategy with high probability. Lastly, we study a dynamic TSP: given a stochastic process that generates targets, is there a policy which guarantees that the number of unvisited targets does not diverge over time? If such stable policies exist, what is the minimum wait for a target? We propose novel stabilizing receding-horizon algorithms whose performances are within a constant factor from the optimum with high probability, in $\real^2$ as well as $\real^3$. We also argue that these algorithms give identical performances for a particular nonholonomic vehicle, Dubins vehicle.
Total Variation Minimization and Graph Cuts for Moving Objects Segmentation
Venue: arXiv cs.CV 2006
Year: 2006

In this paper, we are interested in the application to video segmentation of the discrete shape optimization problem involving the shape weighted perimeter and an additional term depending on a parameter. Based on recent works and in particular the one of Darbon and Sigelle, we justify the equivalence of the shape optimization problem and a weighted total variation regularization. For solving this problem, we adapt the projection algorithm proposed recently for solving the basic TV regularization problem. Another solution to the shape optimization investigated here is the graph cut technique. Both methods have the advantage to lead to a global minimum. Since we can distinguish moving objects from static elements of a scene by analyzing norm of the optical flow vectors, we choose the optical flow norm as initial data. In order to have the contour as close as possible to an edge in the image, we use a classical edge detector function as the weight of the weighted total variation. This model has been used in one of our former works. We also apply the same methods to a video segmentation model used by Jehan-Besson, Barlaud and Aubert. In this case, only standard perimeter is incorporated in the shape functional. We also propose another way for finding moving objects by using an a contrario detection of objects on the image obtained by solving the Rudin-Osher-Fatemi Total Variation regularization problem.We can notice the segmentation can be associated to a level set in the former methods.
Generalized Majority-Minority Operations are Tractable
Venue: arXiv cs.CC 2006
Year: 2006

Generalized majority-minority (GMM) operations are introduced as a common generalization of near unanimity operations and Mal'tsev operations on finite sets. We show that every instance of the constraint satisfaction problem (CSP), where all constraint relations are invariant under a (fixed) GMM operation, is solvable in polynomial time. This constitutes one of the largest tractable cases of the CSP.
Algebraic recognizability of languages
Venue: arXiv cs.LO 2006
Year: 2006

Recognizable languages of finite words are part of every computer science cursus, and they are routinely described as a cornerstone for applications and for theory. We would like to briefly explore why that is, and how this word-related notion extends to more complex models, such as those developed for modeling distributed or timed behaviors.
Approximating Rate-Distortion Graphs of Individual Data: Experiments in Lossy Compression and Denoising
Venue: arXiv cs.IT 2006
Year: 2006

Classical rate-distortion theory requires knowledge of an elusive source distribution. Instead, we analyze rate-distortion properties of individual objects using the recently developed algorithmic rate-distortion theory. The latter is based on the noncomputable notion of Kolmogorov complexity. To apply the theory we approximate the Kolmogorov complexity by standard data compression techniques, and perform a number of experiments with lossy compression and denoising of objects from different domains. We also introduce a natural generalization to lossy compression with side information. To maintain full generality we need to address a difficult searching problem. While our solutions are therefore not time efficient, we do observe good denoising and compression performance.
Using NLP to build the hypertextuel network of a back-of-the-book index
Venue: arXiv cs.AI 2006
Year: 2006

Relying on the idea that back-of-the-book indexes are traditional devices for navigation through large documents, we have developed a method to build a hypertextual network that helps the navigation in a document. Building such an hypertextual network requires selecting a list of descriptors, identifying the relevant text segments to associate with each descriptor and finally ranking the descriptors and reference segments by relevance order. We propose a specific document segmentation method and a relevance measure for information ranking. The algorithms are tested on 4 corpora (of different types and domains) without human intervention or any semantic knowledge.
Event-based Information Extraction for the biomedical domain: the Caderige project
Venue: arXiv cs.AI 2006
Year: 2006

This paper gives an overview of the Caderige project. This project involves teams from different areas (biology, machine learning, natural language processing) in order to develop high-level analysis tools for extracting structured information from biological bibliographical databases, especially Medline. The paper gives an overview of the approach and compares it to the state of the art.
A Semidefinite Relaxation for Air Traffic Flow Scheduling
Venue: arXiv cs.CE 2006
Year: 2006

We first formulate the problem of optimally scheduling air traffic low with sector capacity constraints as a mixed integer linear program. We then use semidefinite relaxation techniques to form a convex relaxation of that problem. Finally, we present a randomization algorithm to further improve the quality of the solution. Because of the specific structure of the air traffic flow problem, the relaxation has a single semidefinite constraint of size dn where d is the maximum delay and n the number of flights.
Simple method to eliminate blur based on Lane and Bates algorithm
Venue: arXiv cs.CV 2006
Year: 2006

A simple search method for finding a blur convolved in a given image is presented. The method can be easily extended to a large blur. The method has been experimentally tested with a model blurred image.
Rapport technique du projet OGRE
Venue: arXiv cs.CL 2006
Year: 2006

This repport concerns automatic understanding of (french) iterative sentences, i.e. sentences where one single verb has to be interpreted by a more or less regular plurality of events. A linguistic analysis is proposed along an extension of Reichenbach's theory, several formal representations are considered and a corpus of 18000 newspaper extracts is described.
Data in the ADS -- Understanding How to Use it Better
Venue: arXiv cs.DL 2006
Year: 2006

The Smithsonian/NASA ADS Abstract Service contains a wealth of data for astronomers and librarians alike, yet the vast majority of usage consists of rudimentary searches. Hints on how to obtain more focused search results by using more of the various capabilities of the ADS are presented, including searching by affiliation. We also discuss the classification of articles by content and by referee status. The ADS is funded by NASA Grant NNG06GG68G-16613687.
Positional Determinacy of Games with Infinitely Many Priorities
Venue: arXiv cs.LO 2006
Year: 2006

We study two-player games of infinite duration that are played on finite or infinite game graphs. A winning strategy for such a game is positional if it only depends on the current position, and not on the history of the play. A game is positionally determined if, from each position, one of the two players has a positional winning strategy. The theory of such games is well studied for winning conditions that are defined in terms of a mapping that assigns to each position a priority from a finite set. Specifically, in Muller games the winner of a play is determined by the set of those priorities that have been seen infinitely often; an important special case are parity games where the least (or greatest) priority occurring infinitely often determines the winner. It is well-known that parity games are positionally determined whereas Muller games are determined via finite-memory strategies. In this paper, we extend this theory to the case of games with infinitely many priorities. Such games arise in several application areas, for instance in pushdown games with winning conditions depending on stack contents. For parity games there are several generalisations to the case of infinitely many priorities. While max-parity games over omega or min-parity games over larger ordinals than omega require strategies with infinite memory, we can prove that min-parity games with priorities in omega are positionally determined. Indeed, it turns out that the min-parity condition over omega is the only infinitary Muller condition that guarantees positional determinacy on all game graphs.
The Application of Fuzzy Logic to the Construction of the Ranking Function of Information Retrieval Systems
Venue: arXiv cs.IR 2006
Year: 2006

The quality of the ranking function is an important factor that determines the quality of the Information Retrieval system. Each document is assigned a score by the ranking function; the score indicates the likelihood of relevance of the document given a query. In the vector space model, the ranking function is defined by a mathematic expression. We propose a fuzzy logic (FL) approach to defining the ranking function. FL provides a convenient way of converting knowledge expressed in a natural language into fuzzy logic rules. The resulting ranking function could be easily viewed, extended, and verified: * if (tf is high) and (idf is high) > (relevance is high); * if (overlap is high) > (relevance is high). By using above FL rules, we are able to achieve performance approximately equal to the state of the art search engine Apache Lucene (deltaP10 +0.92%; deltaMAP -0.1%). The fuzzy logic approach allows combining the logic-based model with the vector model. The resulting model possesses simplicity and formalism of the logic based model, and the flexibility and performance of the vector model.
Farthest-Point Heuristic based Initialization Methods for K-Modes Clustering
Venue: arXiv cs.AI 2006
Year: 2006

The k-modes algorithm has become a popular technique in solving categorical data clustering problems in different application domains. However, the algorithm requires random selection of initial points for the clusters. Different initial points often lead to considerable distinct clustering results. In this paper we present an experimental study on applying a farthest-point heuristic based initialization method to k-modes clustering to improve its performance. Experiments show that new initialization method leads to better clustering accuracy than random selection initialization method for k-modes clustering.
MV3: A new word based stream cipher using rapid mixing and revolving buffers
Venue: arXiv cs.CR 2006
Year: 2006

MV3 is a new word based stream cipher for encrypting long streams of data. A direct adaptation of a byte based cipher such as RC4 into a 32- or 64-bit word version will obviously need vast amounts of memory. This scaling issue necessitates a look for new components and principles, as well as mathematical analysis to justify their use. Our approach, like RC4's, is based on rapidly mixing random walks on directed graphs (that is, walks which reach a random state quickly, from any starting point). We begin with some well understood walks, and then introduce nonlinearity in their steps in order to improve security and show long term statistical correlations are negligible. To minimize the short term correlations, as well as to deter attacks using equations involving successive outputs, we provide a method for sequencing the outputs derived from the walk using three revolving buffers. The cipher is fast -- it runs at a speed of less than 5 cycles per byte on a Pentium IV processor. A word based cipher needs to output more bits per step, which exposes more correlations for attacks. Moreover we seek simplicity of construction and transparent analysis. To meet these requirements, we use a larger state and claim security corresponding to only a fraction of it. Our design is for an adequately secure word-based cipher; our very preliminary estimate puts the security close to exhaustive search for keys of size < 256 bits.
On Geometric Algebra representation of Binary Spatter Codes
Venue: arXiv cs.AI 2006
Year: 2006

Kanerva's Binary Spatter Codes are reformulated in terms of geometric algebra. The key ingredient of the construction is the representation of XOR binding in terms of geometric product.
Peano Count Trees (P-Trees) and Rule Association Mining for Gene Expression Profiling of Microarray Data
Venue: arXiv cs.DS 2006
Year: 2006

The greatest challenge in maximizing the use of gene expression data is to develop new computational tools capable of interconnecting and interpreting the results from different organisms and experimental settings. We propose an integrative and comprehensive approach including a super-chip containing data from microarray experiments collected on different species subjected to hypoxic and anoxic stress. A data mining technology called Peano count tree (P-trees) is used to represent genomic data in multidimensions. Each microarray spot is presented as a pixel with its corresponding red/green intensity feature bands. Each bad is stored separately in a reorganized 8-separate (bSQ) file format. Each bSQ is converted to a quadrant base tree structure (P-tree) from which a superchip is represented as expression P-trees (EP-trees) and repression P-trees (RP-trees). The use of association rule mining is proposed to derived to meanigingfully organize signal transduction pathways taking in consideration evolutionary considerations. We argue that the genetic constitution of an organism (K) can be represented by the total number of genes belonging to two groups. The group X constitutes genes (X1,Xn) and they can be represented as 1 or 0 depending on whether the gene was expressed or not. The second group of Y genes (Y1,Yn) is expressed at different levels. These genes have a very high repression, high expression, very repressed or highly repressed. However, many genes of the group Y are specie specific and modulated by the products and combinations of genes of the group X. In this paper, we introduce the dSQ and P-tree technology; the biological implications of association rule mining using X and Y gene groups and some advances in the integration of this information using the BRAIN architecture.
Partial Evaluation for Program Comprehension
Venue: arXiv cs.SE 2006
Year: 2006

Program comprehension is the most tedious and time consuming task of software maintenance, an important phase of the software life cycle. This is particularly true while maintaining scientific application programs that have been written in Fortran for decades and that are still vital in various domains even though more modern languages are used to implement their user interfaces. Very often, programs have evolved as their application domains increase continually and have become very complex due to extensive modifications. This generality in programs is implemented by input variables whose value does not vary in the context of a given application. Thus, it is very interesting for the maintainer to propagate such information, that is to obtain a simplified program, which behaves like the initial one when used according to the restriction. We have adapted partial evaluation for program comprehension. Our partial evaluator performs mainly two tasks: constant propagation and statements simplification. It includes an interprocedural alias analysis. As our aim is program comprehension rather than optimization, there are two main differences with classical partial evaluation. We do not change the original
On the Secrecy Capacity of Fading Channels
Venue: arXiv cs.IT 2006
Year: 2006

We consider the secure transmission of information over an ergodic fading channel in the presence of an eavesdropper. Our eavesdropper can be viewed as the wireless counterpart of Wyner's wiretapper. The secrecy capacity of such a system is characterized under the assumption of asymptotically long coherence intervals. We first consider the full Channel State Information (CSI) case, where the transmitter has access to the channel gains of the legitimate receiver and the eavesdropper. The secrecy capacity under this full CSI assumption serves as an upper bound for the secrecy capacity when only the CSI of the legitimate receiver is known at the transmitter, which is characterized next. In each scenario, the perfect secrecy capacity is obtained along with the optimal power and rate allocation strategies. We then propose a low-complexity on/off power allocation strategy that achieves near-optimal performance with only the main channel CSI. More specifically, this scheme is shown to be asymptotically optimal as the average SNR goes to infinity, and interestingly, is shown to attain the secrecy capacity under the full CSI assumption. Remarkably, our results reveal the positive impact of fading on the secrecy capacity and establish the critical role of rate adaptation, based on the main channel CSI, in facilitating secure communications over slow fading channels.
ARQ Diversity in Fading Random Access Channels
Venue: arXiv cs.IT 2006
Year: 2006

A cross-layer optimization approach is adopted for the design of symmetric random access wireless systems. Instead of the traditional collision model, a more realistic physical layer model is considered. Based on this model, an Incremental Redundancy Automatic Repeat reQuest (IR-ARQ) scheme, tailored to jointly combat the effects of collisions, multi-path fading, and additive noise, is developed. The Diversity-Multiplexing-Delay tradeoff (DMDT) of the proposed scheme is analyzed for fully-loaded queues, and compared with that of Gallager tree algorithm for collision resolution and the network-assisted diversity multiple access (NDMA) protocol of Tsatsanis et al.. The fully-loaded queue model is then replaced by one with random arrivals, under which these protocols are compared in terms of the stability region, average delay and diversity gain. Overall, our analytical and numerical results establish the superiority of the proposed IR-ARQ scheme and reveal some important insights. For example, it turns out that the performance is optimized, for a given total throughput, by maximizing the probability that a certain user sends a new packet and minimizing the transmission rate employed by each user.
Intrusion detection mechanisms for VoIP applications
Venue: arXiv cs.NI 2006
Year: 2006

VoIP applications are emerging today as an important component in business and communication industry. In this paper, we address the intrusion detection and prevention in VoIP networks and describe how a conceptual solution based on the Bayes inference approach can be used to reinforce the existent security mechanisms. Our approach is based on network monitoring and analyzing of the VoIP-specific traffic. We give a detailed example on attack detection using the SIP signaling protocol.
On the Performance of Lossless Joint Source-Channel Coding Based on Linear Codes
Venue: arXiv cs.IT 2006
Year: 2006

A general lossless joint source-channel coding scheme based on linear codes is proposed and then analyzed in this paper. It is shown that a linear code with good joint spectrum can be used to establish limit-approaching joint source-channel coding schemes for arbitrary sources and channels, where the joint spectrum of the code is a generalization of the input-output weight distribution.
CHAC. A MOACO Algorithm for Computation of Bi-Criteria Military Unit Path in the Battlefield
Venue: arXiv cs.MA 2006
Year: 2006

In this paper we propose a Multi-Objective Ant Colony Optimization (MOACO) algorithm called CHAC, which has been designed to solve the problem of finding the path on a map (corresponding to a simulated battlefield) that minimizes resources while maximizing safety. CHAC has been tested with two different state transition rules: an aggregative function that combines the heuristic and pheromone information of both objectives and a second one that is based on the dominance concept of multiobjective optimization problems. These rules have been evaluated in several different situations (maps with different degree of difficulty), and we have found that they yield better results than a greedy algorithm (taken as baseline) in addition to a military behaviour that is also better in the tactical sense. The aggregative function, in general, yields better results than the one based on dominance.
Scheduling and data redistribution strategies on star platforms
Venue: arXiv cs.DC 2006
Year: 2006

In this work we are interested in the problem of scheduling and redistributing data on master-slave platforms. We consider the case were the workers possess initial loads, some of which having to be redistributed in order to balance their completion times. We examine two different scenarios. The first model assumes that the data consists of independent and identical tasks. We prove the NP-completeness in the strong sense for the general case, and we present two optimal algorithms for special platform types. Furthermore we propose three heuristics for the general case. Simulations consolidate the theoretical results. The second data model is based on Divisible Load Theory. This problem can be solved in polynomial time by a combination of linear programming and simple analytical manipulations.
List Decoding of Hermitian Codes using Groebner Bases
Venue: arXiv cs.IT 2006
Year: 2006

List decoding of Hermitian codes is reformulated to allow an efficient and simple algorithm for the interpolation step. The algorithm is developed using the theory of Groebner bases of modules. The computational complexity of the algorithm seems comparable to previously known algorithms achieving the same task, and the algorithm is better suited for hardware implementation.