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0911.1678
Industrial-Strength Formally Certified SAT Solving
cs.LO cs.AI
Boolean Satisfiability (SAT) solvers are now routinely used in the verification of large industrial problems. However, their application in safety-critical domains such as the railways, avionics, and automotive industries requires some form of assurance for the results, as the solvers can (and sometimes do) have bugs. Unfortunately, the complexity of modern, highly optimized SAT solvers renders impractical the development of direct formal proofs of their correctness. This paper presents an alternative approach where an untrusted, industrial-strength, SAT solver is plugged into a trusted, formally certified, SAT proof checker to provide industrial-strength certified SAT solving. The key novelties and characteristics of our approach are (i) that the checker is automatically extracted from the formal development, (ii), that the combined system can be used as a standalone executable program independent of any supporting theorem prover, and (iii) that the checker certifies any SAT solver respecting the agreed format for satisfiability and unsatisfiability claims. The core of the system is a certified checker for unsatisfiability claims that is formally designed and verified in Coq. We present its formal design and outline the correctness proofs. The actual standalone checker is automatically extracted from the the Coq development. An evaluation of the certified checker on a representative set of industrial benchmarks from the SAT Race Competition shows that, albeit it is slower than uncertified SAT checkers, it is significantly faster than certified checkers implemented on top of an interactive theorem prover.
0911.1685
Multi-Objective Optimisation Method for Posture Prediction and Analysis with Consideration of Fatigue Effect and its Application Case
cs.RO
Automation technique has been widely used in manufacturing industry, but there are still manual handling operations required in assembly and maintenance work in industry. Inappropriate posture and physical fatigue might result in musculoskeletal disorders (MSDs) in such physical jobs. In ergonomics and occupational biomechanics, virtual human modelling techniques have been employed to design and optimize the manual operations in design stage so as to avoid or decrease potential MSD risks. In these methods, physical fatigue is only considered as minimizing the muscle or joint stress, and the fatigue effect along time for the posture is not considered enough. In this study, based on the existing methods and multiple objective optimisation method (MOO), a new posture prediction and analysis method is proposed for predicting the optimal posture and evaluating the physical fatigue in the manual handling operation. The posture prediction and analysis problem is mathematically described and a special application case is demonstrated for analyzing a drilling assembly operation in European Aeronautic Defence & Space Company (EADS) in this paper.
0911.1691
Vertical partitioning of relational OLTP databases using integer programming
cs.DB cs.PF
A way to optimize performance of relational row store databases is to reduce the row widths by vertically partitioning tables into table fractions in order to minimize the number of irrelevant columns/attributes read by each transaction. This paper considers vertical partitioning algorithms for relational row-store OLTP databases with an H-store-like architecture, meaning that we would like to maximize the number of single-sited transactions. We present a model for the vertical partitioning problem that, given a schema together with a vertical partitioning and a workload, estimates the costs (bytes read/written by storage layer access methods and bytes transferred between sites) of evaluating the workload on the given partitioning. The cost model allows for arbitrarily prioritizing load balancing of sites vs. total cost minimization. We show that finding a minimum-cost vertical partitioning in this model is NP-hard and present two algorithms returning solutions in which single-sitedness of read queries is preserved while allowing column replication (which may allow a drastically reduced cost compared to disjoint partitioning). The first algorithm is a quadratic integer program that finds optimal minimum-cost solutions with respect to the model, and the second algorithm is a more scalable heuristic based on simulated annealing. Experiments show that the algorithms can reduce the cost of the model objective by 37% when applied to the TPC-C benchmark and the heuristic is shown to obtain solutions with cost close to the ones found using the quadratic program.
0911.1707
A Dynamic Vulnerability Map to Assess the Risk of Road Network Traffic Utilization
cs.AI physics.soc-ph
Le Havre agglomeration (CODAH) includes 16 establishments classified Seveso with high threshold. In the literature, we construct vulnerability maps to help decision makers assess the risk. Such approaches remain static and do take into account the population displacement in the estimation of the vulnerability. We propose a decision making tool based on a dynamic vulnerability map to evaluate the difficulty of evacuation in the different sectors of CODAH. We use a Geographic Information system (GIS) to visualize the map which evolves with the road traffic state through a detection of communities in large graphs algorithm.
0911.1708
Different goals in multiscale simulations and how to reach them
cs.AI nlin.AO
In this paper we sum up our works on multiscale programs, mainly simulations. We first start with describing what multiscaling is about, how it helps perceiving signal from a background noise in a ?ow of data for example, for a direct perception by a user or for a further use by another program. We then give three examples of multiscale techniques we used in the past, maintaining a summary, using an environmental marker introducing an history in the data and finally using a knowledge on the behavior of the different scales to really handle them at the same time.
0911.1713
Isometries and Construction of Permutation Arrays
math.CO cs.IT math.IT
An (n,d)-permutation code is a subset C of Sym(n) such that the Hamming distance d_H between any two distinct elements of C is at least equal to d. In this paper, we use the characterisation of the isometry group of the metric space (Sym(n),d_H) in order to develop generating algorithms with rejection of isomorphic objects. To classify the (n,d)-permutation codes up to isometry, we construct invariants and study their efficiency. We give the numbers of non-isometric (4,3)- and (5,4)- permutation codes. Maximal and balanced (n,d)-permutation codes are enumerated in a constructive way.
0911.1743
Analysis of peeling decoder for MET ensembles
cs.IT math.IT
The peeling decoder introduced by Luby, et al. allows analysis of LDPC decoding for the binary erasure channel (BEC). For irregular ensembles, they analyze the decoder state as a Markov process and present a solution to the differential equations describing the process mean. Multi-edge type (MET) ensembles allow greater precision through specifying graph connectivity. We generalize the the peeling decoder for MET ensembles and derive analogous differential equations. We offer a new change of variables and solution to the node fraction evolutions in the general (MET) case. This result is preparatory to investigating finite-length ensemble behavior.
0911.1745
Sequence Folding, Lattice Tiling, and Multidimensional Coding
cs.IT math.CO math.IT
Folding a sequence $S$ into a multidimensional box is a well-known method which is used as a multidimensional coding technique. The operation of folding is generalized in a way that the sequence $S$ can be folded into various shapes and not just a box. The new definition of folding is based on a lattice tiling for the given shape $\cS$ and a direction in the $D$-dimensional integer grid. Necessary and sufficient conditions that a lattice tiling for $\cS$ combined with a direction define a folding of a sequence into $\cS$ are derived. The immediate and most impressive application is some new lower bounds on the number of dots in two-dimensional synchronization patterns. This can be also generalized for multidimensional synchronization patterns. The technique and its application for two-dimensional synchronization patterns, raise some interesting problems in discrete geometry. We will also discuss these problems. It is also shown how folding can be used to construct multidimensional error-correcting codes. Finally, by using the new definition of folding, multidimensional pseudo-random arrays with various shapes are generated.
0911.1763
The Replicator Equation as an Inference Dynamic
math.DS cs.IT math.IT
The replicator equation is interpreted as a continuous inference equation and a formal similarity between the discrete replicator equation and Bayesian inference is described. Further connections between inference and the replicator equation are given including a discussion of information divergences and exponential families as solutions for the replicator dynamic, using Fisher information and information geometry.
0911.1764
Escort Evolutionary Game Theory
math.DS cs.IT math.DG math.IT
A family of replicator-like dynamics, called the escort replicator equation, is constructed using information-geometric concepts and generalized information entropies and diverenges from statistical thermodynamics. Lyapunov functions and escort generalizations of basic concepts and constructions in evolutionary game theory are given, such as an escorted Fisher's Fundamental theorem and generalizations of the Shahshahani geometry.
0911.1813
Interactive Privacy via the Median Mechanism
cs.CR cs.CC cs.DB cs.DS
We define a new interactive differentially private mechanism -- the median mechanism -- for answering arbitrary predicate queries that arrive online. Relative to fixed accuracy and privacy constraints, this mechanism can answer exponentially more queries than the previously best known interactive privacy mechanism (the Laplace mechanism, which independently perturbs each query result). Our guarantee is almost the best possible, even for non-interactive privacy mechanisms. Conceptually, the median mechanism is the first privacy mechanism capable of identifying and exploiting correlations among queries in an interactive setting. We also give an efficient implementation of the median mechanism, with running time polynomial in the number of queries, the database size, and the domain size. This efficient implementation guarantees privacy for all input databases, and accurate query results for almost all input databases. The dependence of the privacy on the number of queries in this mechanism improves over that of the best previously known efficient mechanism by a super-polynomial factor, even in the non-interactive setting.
0911.1826
Arithmetic completely regular codes
math.CO cs.IT math.IT
In this paper, we explore completely regular codes in the Hamming graphs and related graphs. Experimental evidence suggests that many completely regular codes have the property that the eigenvalues of the code are in arithmetic progression. In order to better understand these "arithmetic completely regular codes", we focus on cartesian products of completely regular codes and products of their corresponding coset graphs in the additive case. Employing earlier results, we are then able to prove a theorem which nearly classifies these codes in the case where the graph admits a completely regular partition into such codes (e.g, the cosets of some additive completely regular code). Connections to the theory of distance-regular graphs are explored and several open questions are posed.
0911.1842
Standards for Language Resources
cs.CL
The goal of this paper is two-fold: to present 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.
0911.1849
The Feasibility of Interference Alignment over Measured MIMO-OFDM Channels
cs.IT math.IT
Interference alignment (IA) has been shown to achieve the maximum achievable degrees of freedom in the interference channel. This results in sum rate scaling linearly with the number of users in the high signal-to-noise-ratio (SNR) regime. Linear scaling is achieved by precoding transmitted signals to align interference subspaces at the receivers, given channel knowledge of all transmit-receive pairs, effectively reducing the number of discernible interferers. The theory of IA was derived under assumptions about the richness of scattering in the propagation channel; practical channels do not guarantee such ideal characteristics. This paper presents the first experimental study of IA in measured multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) interference channels. Our measurement campaign includes a variety of indoor and outdoor measurement scenarios at The University of Texas at Austin. We show that IA achieves the claimed scaling factors, or degrees of freedom, in several measured channel settings for a 3 user, 2 antennas per node setup. In addition to verifying the claimed performance, we characterize the effect of Kronecker spatial correlation on sum rate and present two other correlation measures, which we show are more tightly related to the achieved sum rate.
0911.1934
On a Gel'fand-Yaglom-Peres theorem for f-divergences
cs.IT math.IT math.ST stat.TH
It is shown that the $f$-divergence between two probability measures $P$ and $R$ equals the supremum of the same $f$-divergence computed over all finite measurable partitions of the original space, thus generalizing results previously proved by Gel'fand and Yaglom and by Peres for the Information Divergence and more recently by Dukkipati, Bhatnagar and Murty for the Tsallis' and Renyi's divergences.
0911.1965
Active Learning for Mention Detection: A Comparison of Sentence Selection Strategies
cs.CL cs.AI
We propose and compare various sentence selection strategies for active learning for the task of detecting mentions of entities. The best strategy employs the sum of confidences of two statistical classifiers trained on different views of the data. Our experimental results show that, compared to the random selection strategy, this strategy reduces the amount of required labeled training data by over 50% while achieving the same performance. The effect is even more significant when only named mentions are considered: the system achieves the same performance by using only 42% of the training data required by the random selection strategy.
0911.2022
Interference Channels With Arbitrarily Correlated Sources
cs.IT math.IT
Communicating arbitrarily correlated sources over interference channels is considered in this paper. A sufficient condition is found for the lossless transmission of a pair of correlated sources over a discrete memoryless interference channel. With independent sources, the sufficient condition reduces to the Han-Kobayashi achievable rate region for the interference channel. For a special correlation structure (in the sense of Slepian-Wolf, 1973), the proposed region reduces to the known achievable region for interference channels with common information. A simple example is given to show that the separation approach, with Slepian-Wolf encoding followed by optimal channel coding, is strictly suboptimal.
0911.2023
Opportunistic capacity and error exponent regions for compound channel with feedback
cs.IT math.IT
Variable length communication over a compound channel with feedback is considered. Traditionally, capacity of a compound channel without feedback is defined as the maximum rate that is determined before the start of communication such that communication is reliable. This traditional definition is pessimistic. In the presence of feedback, an opportunistic definition is given. Capacity is defined as the maximum rate that is determined at the end of communication such that communication is reliable. Thus, the transmission rate can adapt to the channel chosen by nature. Under this definition, feedback communication over a compound channel is conceptually similar to multi-terminal communication. Transmission rate is a vector rather than a scalar; channel capacity is a region rather than a scalar; error exponent is a region rather than a scalar. In this paper, variable length communication over a compound channel with feedback is formulated, its opportunistic capacity region is characterized, and lower bounds for its error exponent region are provided..
0911.2053
Interference Mitigation Through Limited Receiver Cooperation
cs.IT math.IT
Interference is a major issue limiting the performance in wireless networks. Cooperation among receivers can help mitigate interference by forming distributed MIMO systems. The rate at which receivers cooperate, however, is limited in most scenarios. How much interference can one bit of receiver cooperation mitigate? In this paper, we study the two-user Gaussian interference channel with conferencing decoders to answer this question in a simple setting. We identify two regions regarding the gain from receiver cooperation: linear and saturation regions. In the linear region receiver cooperation is efficient and provides a degrees-of-freedom gain, which is either one cooperation bit buys one more bit or two cooperation bits buy one more bit until saturation. In the saturation region receiver cooperation is inefficient and provides a power gain, which is at most a constant regardless of the rate at which receivers cooperate. The conclusion is drawn from the characterization of capacity region to within two bits. The proposed strategy consists of two parts: (1) the transmission scheme, where superposition encoding with a simple power split is employed, and (2) the cooperative protocol, where one receiver quantize-bin-and-forwards its received signal, and the other after receiving the side information decode-bin-and-forwards its received signal.
0911.2197
On the relation between plausibility logic and the maximum-entropy principle: a numerical study
math.PR cs.IT math.IT physics.data-an
What is the relationship between plausibility logic and the principle of maximum entropy? When does the principle give unreasonable or wrong results? When is it appropriate to use the rule `expectation = average'? Can plausibility logic give the same answers as the principle, and better answers if those of the principle are unreasonable? To try to answer these questions, this study offers a numerical collection of plausibility distributions given by the maximum-entropy principle and by plausibility logic for a set of fifteen simple problems: throwing dice.
0911.2258
Discrete Hamilton-Jacobi Theory
math.OC cs.SY
We develop a discrete analogue of Hamilton-Jacobi theory in the framework of discrete Hamiltonian mechanics. The resulting discrete Hamilton-Jacobi equation is discrete only in time. We describe a discrete analogue of Jacobi's solution and also prove a discrete version of the geometric Hamilton-Jacobi theorem. The theory applied to discrete linear Hamiltonian systems yields the discrete Riccati equation as a special case of the discrete Hamilton-Jacobi equation. We also apply the theory to discrete optimal control problems, and recover some well-known results, such as the Bellman equation (discrete-time HJB equation) of dynamic programming and its relation to the costate variable in the Pontryagin maximum principle. This relationship between the discrete Hamilton-Jacobi equation and Bellman equation is exploited to derive a generalized form of the Bellman equation that has controls at internal stages.
0911.2280
PageRank Optimization by Edge Selection
cs.DS cs.CC cs.SI
The importance of a node in a directed graph can be measured by its PageRank. The PageRank of a node is used in a number of application contexts - including ranking websites - and can be interpreted as the average portion of time spent at the node by an infinite random walk. We consider the problem of maximizing the PageRank of a node by selecting some of the edges from a set of edges that are under our control. By applying results from Markov decision theory, we show that an optimal solution to this problem can be found in polynomial time. Our core solution results in a linear programming formulation, but we also provide an alternative greedy algorithm, a variant of policy iteration, which runs in polynomial time, as well. Finally, we show that, under the slight modification for which we are given mutually exclusive pairs of edges, the problem of PageRank optimization becomes NP-hard.
0911.2284
A New Look at the Classical Entropy of Written English
cs.CL
A simple method for finding the entropy and redundancy of a reasonable long sample of English text by direct computer processing and from first principles according to Shannon theory is presented. As an example, results on the entropy of the English language have been obtained based on a total of 20.3 million characters of written English, considering symbols from one to five hundred characters in length. Besides a more realistic value of the entropy of English, a new perspective on some classic entropy-related concepts is presented. This method can also be extended to other Latin languages. Some implications for practical applications such as plagiarism-detection software, and the minimum number of words that should be used in social Internet network messaging, are discussed.
0911.2323
A Type System for Required/Excluded Elements in CLS
cs.LO cs.CE
The calculus of looping sequences is a formalism for describing the evolution of biological systems by means of term rewriting rules. We enrich this calculus with a type discipline to guarantee the soundness of reduction rules with respect to some biological properties deriving from the requirement of certain elements, and the repellency of others. As an example, we model a toy system where the repellency of a certain element is captured by our type system and forbids another element to exit a compartment.
0911.2324
Deterministic Autopoietic Automata
cs.NE cs.FL
This paper studies two issues related to the paper on Computing by Self-reproduction: Autopoietic Automata by Jiri Wiedermann. It is shown that all results presented there extend to deterministic computations. In particular, nondeterminism is not needed for a lineage to generate all autopoietic automata.
0911.2327
An Intuitive Automated Modelling Interface for Systems Biology
cs.PL cs.CE cs.LO q-bio.QM
We introduce a natural language interface for building stochastic pi calculus models of biological systems. In this language, complex constructs describing biochemical events are built from basic primitives of association, dissociation and transformation. This language thus allows us to model biochemical systems modularly by describing their dynamics in a narrative-style language, while making amendments, refinements and extensions on the models easy. We demonstrate the language on a model of Fc-gamma receptor phosphorylation during phagocytosis. We provide a tool implementation of the translation into a stochastic pi calculus language, Microsoft Research's SPiM.
0911.2330
Diffusion Controlled Reactions, Fluctuation Dominated Kinetics, and Living Cell Biochemistry
cs.CE cs.OH q-bio.QM
In recent years considerable portion of the computer science community has focused its attention on understanding living cell biochemistry and efforts to understand such complication reaction environment have spread over wide front, ranging from systems biology approaches, through network analysis (motif identification) towards developing language and simulators for low level biochemical processes. Apart from simulation work, much of the efforts are directed to using mean field equations (equivalent to the equations of classical chemical kinetics) to address various problems (stability, robustness, sensitivity analysis, etc.). Rarely is the use of mean field equations questioned. This review will provide a brief overview of the situations when mean field equations fail and should not be used. These equations can be derived from the theory of diffusion controlled reactions, and emerge when assumption of perfect mixing is used.
0911.2346
Asymmetric Multilevel Diversity Coding and Asymmetric Gaussian Multiple Descriptions
cs.IT math.IT
We consider the asymmetric multilevel diversity (A-MLD) coding problem, where a set of $2^K-1$ information sources, ordered in a decreasing level of importance, is encoded into $K$ messages (or descriptions). There are $2^K-1$ decoders, each of which has access to a non-empty subset of the encoded messages. Each decoder is required to reproduce the information sources up to a certain importance level depending on the combination of descriptions available to it. We obtain a single letter characterization of the achievable rate region for the 3-description problem. In contrast to symmetric multilevel diversity coding, source-separation coding is not sufficient in the asymmetric case, and ideas akin to network coding need to be used strategically. Based on the intuitions gained in treating the A-MLD problem, we derive inner and outer bounds for the rate region of the asymmetric Gaussian multiple description (MD) problem with three descriptions. Both the inner and outer bounds have a similar geometric structure to the rate region template of the A-MLD coding problem, and moreover, we show that the gap between them is small, which results in an approximate characterization of the asymmetric Gaussian three description rate region.
0911.2381
Analytical Determination of Fractal Structure in Stochastic Time Series
physics.data-an cond-mat.stat-mech cs.LG nlin.CD stat.ME
Current methods for determining whether a time series exhibits fractal structure (FS) rely on subjective assessments on estimators of the Hurst exponent (H). Here, I introduce the Bayesian Assessment of Scaling, an analytical framework for drawing objective and accurate inferences on the FS of time series. The technique exploits the scaling property of the diffusion associated to a time series. The resulting criterion is simple to compute and represents an accurate characterization of the evidence supporting different hypotheses on the scaling regime of a time series. Additionally, a closed-form Maximum Likelihood estimator of H is derived from the criterion, and this estimator outperforms the best available estimators.
0911.2390
How Creative Should Creators Be To Optimize the Evolution of Ideas? A Computational Model
cs.AI cs.NE physics.soc-ph
There are both benefits and drawbacks to creativity. In a social group it is not necessary for all members to be creative to benefit from creativity; some merely imitate or enjoy the fruits of others' creative efforts. What proportion should be creative? This paper contains a very preliminary investigation of this question carried out using a computer model of cultural evolution referred to as EVOC (for EVOlution of Culture). EVOC is composed of neural network based agents that evolve fitter ideas for actions by (1) inventing new ideas through modification of existing ones, and (2) imitating neighbors' ideas. The ideal proportion with respect to fitness of ideas occurs when thirty to forty percent of the individuals is creative. When creators are inventing 50% of iterations or less, mean fitness of actions in the society is a positive function of the ratio of creators to imitators; otherwise mean fitness of actions starts to drop when the ratio of creators to imitators exceeds approximately 30%. For all levels or creativity, the diversity of ideas in a population is positively correlated with the ratio of creative agents.
0911.2405
Emotion: Appraisal-coping model for the "Cascades" problem
cs.AI
Modelling emotion has become a challenge nowadays. Therefore, several models have been produced in order to express human emotional activity. However, only a few of them are currently able to express the close relationship existing between emotion and cognition. An appraisal-coping model is presented here, with the aim to simulate the emotional impact caused by the evaluation of a particular situation (appraisal), along with the consequent cognitive reaction intended to face the situation (coping). This model is applied to the "Cascades" problem, a small arithmetical exercise designed for ten-year-old pupils. The goal is to create a model corresponding to a child's behaviour when solving the problem using his own strategies.
0911.2501
Emotion : mod\`ele d'appraisal-coping pour le probl\`eme des Cascades
cs.AI
Modeling emotion has become a challenge nowadays. Therefore, several models have been produced in order to express human emotional activity. However, only a few of them are currently able to express the close relationship existing between emotion and cognition. An appraisal-coping model is presented here, with the aim to simulate the emotional impact caused by the evaluation of a particular situation (appraisal), along with the consequent cognitive reaction intended to face the situation (coping). This model is applied to the ?Cascades? problem, a small arithmetical exercise designed for ten-year-old pupils. The goal is to create a model corresponding to a child's behavior when solving the problem using his own strategies.
0911.2551
Minimax Robust Quickest Change Detection
cs.IT math.IT math.ST stat.TH
The popular criteria of optimality for quickest change detection procedures are the Lorden criterion, the Shiryaev-Roberts-Pollak criterion, and the Bayesian criterion. In this paper a robust version of these quickest change detection problems is considered when the pre-change and post-change distributions are not known exactly but belong to known uncertainty classes of distributions. For uncertainty classes that satisfy a specific condition, it is shown that one can identify least favorable distributions (LFDs) from the uncertainty classes, such that the detection rule designed for the LFDs is optimal for the robust problem in a minimax sense. The condition is similar to that required for the identification of LFDs for the robust hypothesis testing problem originally studied by Huber. An upper bound on the delay incurred by the robust test is also obtained in the asymptotic setting under the Lorden criterion of optimality. This bound quantifies the delay penalty incurred to guarantee robustness. When the LFDs can be identified, the proposed test is easier to implement than the CUSUM test based on the Generalized Likelihood Ratio (GLR) statistic which is a popular approach for such robust change detection problems. The proposed test is also shown to give better performance than the GLR test in simulations for some parameter values.
0911.2564
Distributed Coalition Formation Games for Secure Wireless Transmission
cs.IT math.IT
Cooperation among wireless nodes has been recently proposed for improving the physical layer (PHY) security of wireless transmission in the presence of multiple eavesdroppers. While existing PHY security literature answered the question ``what are the link-level secrecy rate gains from cooperation?'', this paper attempts to answer the question of ``how to achieve those gains in a practical decentralized wireless network and in the presence of a cost for information exchange?''. For this purpose, we model the PHY security cooperation problem as a coalitional game with non-transferable utility and propose a distributed algorithm for coalition formation. Through the proposed algorithm, the wireless users can cooperate and self-organize into disjoint independent coalitions, while maximizing their secrecy rate taking into account the security costs during information exchange. We analyze the resulting coalitional structures for both decode-and-forward and amplify-and-forward cooperation and study how the users can adapt the network topology to environmental changes such as mobility. Through simulations, we assess the performance of the proposed algorithm and show that, by coalition formation using decode-and-forward, the average secrecy rate per user is increased of up to 25.3 % and 24.4 % (for a network with 45 users) relative to the non-cooperative and amplify-and-forward cases, respectively.
0911.2632
Measuring contextual citation impact of scientific journals
cs.DL cs.IR
This paper explores a new indicator of journal citation impact, denoted as source normalized impact per paper (SNIP). It measures a journal's contextual citation impact, taking into account characteristics of its properly defined subject field, especially the frequency at which authors cite other papers in their reference lists, the rapidity of maturing of citation impact, and the extent to which a database used for the assessment covers the field's literature. It further develops Eugene Garfield's notions of a field's 'citation potential' defined as the average length of references lists in a field and determining the probability of being cited, and the need in fair performance assessments to correct for differences between subject fields. A journal's subject field is defined as the set of papers citing that journal. SNIP is defined as the ratio of the journal's citation count per paper and the citation potential in its subject field. It aims to allow direct comparison of sources in different subject fields. Citation potential is shown to vary not only between journal subject categories - groupings of journals sharing a research field - or disciplines (e.g., journals in mathematics, engineering and social sciences tend to have lower values than titles in life sciences), but also between journals within the same subject category. For instance, basic journals tend to show higher citation potentials than applied or clinical journals, and journals covering emerging topics higher than periodicals in classical subjects or more general journals. SNIP corrects for such differences. Its strengths and limitations are critically discussed, and suggestions are made for further research. All empirical results are derived from Elsevier's Scopus.
0911.2746
Model Selection: Two Fundamental Measures of Coherence and Their Algorithmic Significance
cs.IT math.IT math.ST stat.TH
The problem of model selection arises in a number of contexts, such as compressed sensing, subset selection in linear regression, estimation of structures in graphical models, and signal denoising. This paper generalizes the notion of \emph{incoherence} in the existing literature on model selection and introduces two fundamental measures of coherence---termed as the worst-case coherence and the average coherence---among the columns of a design matrix. In particular, it utilizes these two measures of coherence to provide an in-depth analysis of a simple one-step thresholding (OST) algorithm for model selection. One of the key insights offered by the ensuing analysis is that OST is feasible for model selection as long as the design matrix obeys an easily verifiable property. In addition, the paper also characterizes the model-selection performance of OST in terms of the worst-case coherence, \mu, and establishes that OST performs near-optimally in the low signal-to-noise ratio regime for N x C design matrices with \mu = O(N^{-1/2}). Finally, in contrast to some of the existing literature on model selection, the analysis in the paper is nonasymptotic in nature, it does not require knowledge of the true model order, it is applicable to generic (random or deterministic) design matrices, and it neither requires submatrices of the design matrix to have full rank, nor does it assume a statistical prior on the values of the nonzero entries of the data vector.
0911.2784
On Bregman Distances and Divergences of Probability Measures
cs.IT math.IT math.PR math.ST stat.TH
The paper introduces scaled Bregman distances of probability distributions which admit non-uniform contributions of observed events. They are introduced in a general form covering not only the distances of discrete and continuous stochastic observations, but also the distances of random processes and signals. It is shown that the scaled Bregman distances extend not only the classical ones studied in the previous literature, but also the information divergence and the related wider class of convex divergences of probability measures. An information processing theorem is established too, but only in the sense of invariance w.r.t. statistically sufficient transformations and not in the sense of universal monotonicity. Pathological situations where coding can increase the classical Bregman distance are illustrated by a concrete example. In addition to the classical areas of application of the Bregman distances and convex divergences such as recognition, classification, learning and evaluation of proximity of various features and signals, the paper mentions a new application in 3D-exploratory data analysis. Explicit expressions for the scaled Bregman distances are obtained in general exponential families, with concrete applications in the binomial, Poisson and Rayleigh families, and in the families of exponential processes such as the Poisson and diffusion processes including the classical examples of the Wiener process and geometric Brownian motion.
0911.2829
Proceedings Fifth Workshop on Developments in Computational Models--Computational Models From Nature
cs.CE cs.AI cs.CC cs.FL cs.LO cs.NE cs.PL
The special theme of DCM 2009, co-located with ICALP 2009, concerned Computational Models From Nature, with a particular emphasis on computational models derived from physics and biology. The intention was to bring together different approaches - in a community with a strong foundational background as proffered by the ICALP attendees - to create inspirational cross-boundary exchanges, and to lead to innovative further research. Specifically DCM 2009 sought contributions in quantum computation and information, probabilistic models, chemical, biological and bio-inspired ones, including spatial models, growth models and models of self-assembly. Contributions putting to the test logical or algorithmic aspects of computing (e.g., continuous computing with dynamical systems, or solid state computing models) were also very much welcomed.
0911.2847
Cooperative Precoding/Resource Allocation Games under Spectral Mask and Total Power Constraints
cs.IT math.IT
The use of orthogonal signaling schemes such as time-, frequency-, or code-division multiplexing (T-, F-, CDM) in multi-user systems allows for power-efficient simple receivers. It is shown in this paper that by using orthogonal signaling on frequency selective fading channels, the cooperative Nash bargaining (NB)-based precoding games for multi-user systems, which aim at maximizing the information rates of all users, are simplified to the corresponding cooperative resource allocation games. The latter provides additional practically desired simplifications to transmitter design and significantly reduces the overhead during user cooperation. The complexity of the corresponding precoding/resource allocation games, however, depends on the constraints imposed on the users. If only spectral mask constraints are present, the corresponding cooperative NB problem can be formulated as a convex optimization problem and solved efficiently in a distributed manner using dual decomposition based algorithm. However, the NB problem is non-convex if total power constraints are also imposed on the users. In this case, the complexity associate with finding the NB solution is unacceptably high. Therefore, the multi-user systems are categorized into bandwidth- and power-dominant based on a bottleneck resource, and different manners of cooperation are developed for each type of systems for the case of two-users. Such classification guarantees that the solution obtained in each case is Pareto-optimal and actually can be identical to the optimal solution, while the complexity is significantly reduced. Simulation results demonstrate the efficiency of the proposed cooperative precoding/resource allocation strategies and the reduced complexity of the proposed algorithms.
0911.2865
Neural Networks for Dynamic Shortest Path Routing Problems - A Survey
cs.NE cs.AI
This paper reviews the overview of the dynamic shortest path routing problem and the various neural networks to solve it. Different shortest path optimization problems can be solved by using various neural networks algorithms. The routing in packet switched multi-hop networks can be described as a classical combinatorial optimization problem i.e. a shortest path routing problem in graphs. The survey shows that the neural networks are the best candidates for the optimization of dynamic shortest path routing problems due to their fastness in computation comparing to other softcomputing and metaheuristics algorithms
0911.2873
Relating Granger causality to directed information theory for networks of stochastic processes
cs.IT math.IT
This paper addresses the problem of inferring circulation of information between multiple stochastic processes. We discuss two possible frameworks in which the problem can be studied: directed information theory and Granger causality. The main goal of the paper is to study the connection between these two frameworks. In the case of directed information theory, we stress the importance of Kramer's causal conditioning. This type of conditioning is necessary not only in the definition of the directed information but also for handling causal side information. We also show how directed information decomposes into the sum of two measures, the first one related to Schreiber's transfer entropy quantifies the dynamical aspects of causality, whereas the second one, termed instantaneous information exchange, quantifies the instantaneous aspect of causality. After having recalled the definition of Granger causality, we establish its connection with directed information theory. The connection is particularly studied in the Gaussian case, showing that Geweke's measures of Granger causality correspond to the transfer entropy and the instantaneous information exchange. This allows to propose an information theoretic formulation of Granger causality.
0911.2889
Global communications in multiprocessor simulations of flames
cs.DC cs.CE cs.MS cs.PF
In this paper we investigate performance of global communications in a particular parallel code. The code simulates dynamics of expansion of premixed spherical flames using an asymptotic model of Sivashinsky type and a spectral numerical algorithm. As a result, the code heavily relies on global all-to-all interprocessor communications implementing transposition of the distributed data array in which numerical solution to the problem is stored. This global data interdependence makes interprocessor connectivity of the HPC system as important as the floating-point power of the processors of which the system is built. Our experiments show that efficient numerical simulation of this particular model, with global data interdependence, on modern HPC systems is possible. Prospects of performance of more sophisticated models of flame dynamics are analysed as well.
0911.2900
Computation Speed of the F.A.S.T. Model
cs.MA physics.soc-ph
The F.A.S.T. model for microscopic simulation of pedestrians was formulated with the idea of parallelizability and small computation times in general in mind, but so far it was never demonstrated, if it can in fact be implemented efficiently for execution on a multi-core or multi-CPU system. In this contribution results are given on computation times for the F.A.S.T. model on an eight-core PC.
0911.2902
Simulation of Pedestrians Crossing a Street
cs.MA
The simulation of vehicular traffic as well as pedestrian dynamics meanwhile both have a decades long history. The success of this conference series, PED and others show that the interest in these topics is still strongly increasing. This contribution deals with a combination of both systems: pedestrians crossing a street. In a VISSIM simulation for varying demand jam sizes of vehicles as well as pedestrians and the travel times of the pedestrians are measured and compared. The study is considered as a study of VISSIM's con ict area functionality as such, as there is no empirical data available to use for calibration issues. Above a vehicle demand threshold the results show a non-monotonic dependence of pedestrians' travel time on pedestrian demand.
0911.2904
Sequential anomaly detection in the presence of noise and limited feedback
cs.LG
This paper describes a methodology for detecting anomalies from sequentially observed and potentially noisy data. The proposed approach consists of two main elements: (1) {\em filtering}, or assigning a belief or likelihood to each successive measurement based upon our ability to predict it from previous noisy observations, and (2) {\em hedging}, or flagging potential anomalies by comparing the current belief against a time-varying and data-adaptive threshold. The threshold is adjusted based on the available feedback from an end user. Our algorithms, which combine universal prediction with recent work on online convex programming, do not require computing posterior distributions given all current observations and involve simple primal-dual parameter updates. At the heart of the proposed approach lie exponential-family models which can be used in a wide variety of contexts and applications, and which yield methods that achieve sublinear per-round regret against both static and slowly varying product distributions with marginals drawn from the same exponential family. Moreover, the regret against static distributions coincides with the minimax value of the corresponding online strongly convex game. We also prove bounds on the number of mistakes made during the hedging step relative to the best offline choice of the threshold with access to all estimated beliefs and feedback signals. We validate the theory on synthetic data drawn from a time-varying distribution over binary vectors of high dimensionality, as well as on the Enron email dataset.
0911.2922
Sparse Eigenvectors of the Discrete Fourier Transform
cs.IT math.IT
We construct a basis of sparse eigenvectors for the N-dimensional discrete Fourier transform. The sparsity differs from the optimal by at most a factor of four. When N is a perfect square, the basis is orthogonal.
0911.2942
Breaching Euclidean Distance-Preserving Data Perturbation Using Few Known Inputs
cs.DB cs.CR
We examine Euclidean distance-preserving data perturbation as a tool for privacy-preserving data mining. Such perturbations allow many important data mining algorithms e.g. hierarchical and k-means clustering), with only minor modification, to be applied to the perturbed data and produce exactly the same results as if applied to the original data. However, the issue of how well the privacy of the original data is preserved needs careful study. We engage in this study by assuming the role of an attacker armed with a small set of known original data tuples (inputs). Little work has been done examining this kind of attack when the number of known original tuples is less than the number of data dimensions. We focus on this important case, develop and rigorously analyze an attack that utilizes any number of known original tuples. The approach allows the attacker to estimate the original data tuple associated with each perturbed tuple and calculate the probability that the estimation results in a privacy breach. On a real 16-dimensional dataset, we show that the attacker, with 4 known original tuples, can estimate an original unknown tuple with less than 7% error with probability exceeding 0.8.
0911.2948
Spatial Analysis of Opportunistic Downlink Relaying in a Two-Hop Cellular System
cs.IT cs.NI math.IT stat.ME
We consider a two-hop cellular system in which the mobile nodes help the base station by relaying information to the dead spots. While two-hop cellular schemes have been analyzed previously, the distribution of the node locations has not been explicitly taken into account. In this paper, we model the node locations of the base stations and the mobile stations as a point process on the plane and then analyze the performance of two different two-hop schemes in the downlink. In one scheme the node nearest to the destination that has decoded information from the base station in the first hop is used as the relay. In the second scheme the node with the best channel to the relay that received information in the first hop acts as a relay. In both these schemes we obtain the success probability of the two hop scheme, accounting for the interference from all other cells. We use tools from stochastic geometry and point process theory to analyze the two hop schemes. Besides the results obtained a main contribution of the paper is to introduce a mathematical framework that can be used to analyze arbitrary relaying schemes. Some of the main contributions of this paper are the analytical techniques introduced for the inclusion of the spatial locations of the nodes into the mathematical analysis.
0911.2952
Cooperative Feedback for Multi-Antenna Cognitive Radio Networks
cs.IT math.IT
Cognitive beamforming (CB) is a multi-antenna technique for efficient spectrum sharing between primary users (PUs) and secondary users (SUs) in a cognitive radio network. Specifically, a multi-antenna SU transmitter applies CB to suppress the interference to the PU receivers as well as enhance the corresponding SU-link performance. In this paper, for a multiple-input-single-output (MISO) SU channel coexisting with a single-input-single-output (SISO) PU channel, we propose a new and practical paradigm for designing CB based on the finite-rate cooperative feedback from the PU receiver to the SU transmitter. Specifically, the PU receiver communicates to the SU transmitter the quantized SU-to-PU channel direction information (CDI) for computing the SU transmit beamformer, and the interference power control (IPC) signal that regulates the SU transmission power according to the tolerable interference margin at the PU receiver. Two CB algorithms based on cooperative feedback are proposed: one restricts the SU transmit beamformer to be orthogonal to the quantized SU-to-PU channel direction and the other relaxes such a constraint. In addition, cooperative feedforward of the SU CDI from the SU transmitter to the PU receiver is exploited to allow more efficient cooperative feedback. The outage probabilities of the SU link for different CB and cooperative feedback/feedforward algorithms are analyzed, from which the optimal bit-allocation tradeoff between the CDI and IPC feedback is characterized.
0911.2974
A Dynamic Near-Optimal Algorithm for Online Linear Programming
cs.DS cs.LG
A natural optimization model that formulates many online resource allocation and revenue management problems is the online linear program (LP) in which the constraint matrix is revealed column by column along with the corresponding objective coefficient. In such a model, a decision variable has to be set each time a column is revealed without observing the future inputs and the goal is to maximize the overall objective function. In this paper, we provide a near-optimal algorithm for this general class of online problems under the assumption of random order of arrival and some mild conditions on the size of the LP right-hand-side input. Specifically, our learning-based algorithm works by dynamically updating a threshold price vector at geometric time intervals, where the dual prices learned from the revealed columns in the previous period are used to determine the sequential decisions in the current period. Due to the feature of dynamic learning, the competitiveness of our algorithm improves over the past study of the same problem. We also present a worst-case example showing that the performance of our algorithm is near-optimal.
0911.3108
On game psychology: an experiment on the chess board/screen, should you always "do your best", and why the programs with prescribed weaknesses cannot be our good friends?
cs.AI cs.GT math.HO
It is noted that some unusual moves against a strong chess program greatly weaken its ability to see the serious targets of the game, and its whole level of play... It is suggested to create programs with different weaknesses in order to analyze similar human behavior. Finally, a new version of chess, "Chess Corrida" is suggested.
0911.3125
A computational model of the bottlenose dolphin sonar: Feature-extracting method
cs.CE
The data describing a process of echo-image formation in bottlenose dolphin sonar perception were accumulated in our experimental explorations. These data were formalized mathematically and used in the computational model, comparative testing of which in echo-discrimination tasks revealed no less capabilities then those of bottlenose dolphins.
0911.3209
Apply Ant Colony Algorithm to Search All Extreme Points of Function
cs.AI cs.NE
To find all extreme points of multimodal functions is called extremum problem, which is a well known difficult issue in optimization fields. Applying ant colony optimization (ACO) to solve this problem is rarely reported. The method of applying ACO to solve extremum problem is explored in this paper. Experiment shows that the solution error of the method presented in this paper is less than 10^-8. keywords: Extremum Problem; Ant Colony Optimization (ACO)
0911.3213
Optimum estimation via gradients of partition functions and information measures: a statistical-mechanical perspective
cs.IT math.IT
In continuation to a recent work on the statistical--mechanical analysis of minimum mean square error (MMSE) estimation in Gaussian noise via its relation to the mutual information (the I-MMSE relation), here we propose a simple and more direct relationship between optimum estimation and certain information measures (e.g., the information density and the Fisher information), which can be viewed as partition functions and hence are amenable to analysis using statistical--mechanical techniques. The proposed approach has several advantages, most notably, its applicability to general sources and channels, as opposed to the I-MMSE relation and its variants which hold only for certain classes of channels (e.g., additive white Gaussian noise channels). We then demonstrate the derivation of the conditional mean estimator and the MMSE in a few examples. Two of these examples turn out to be generalizable to a fairly wide class of sources and channels. For this class, the proposed approach is shown to yield an approximate conditional mean estimator and an MMSE formula that has the flavor of a single-letter expression. We also show how our approach can easily be generalized to situations of mismatched estimation.
0911.3241
Optimal Control in Two-Hop Relay Routing
cs.NI cs.IT math.IT
We study the optimal control of propagation of packets in delay tolerant mobile ad-hoc networks. We consider a two-hop forwarding policy under which the expected number of nodes carrying copies of the packets obeys a linear dynamics. We exploit this property to formulate the problem in the framework of linear quadratic optimal control which allows us to obtain closed-form expressions for the optimal control and to study numerically the tradeoffs by varying various parameters that define the cost.
0911.3256
Enumerative Coding for Grassmannian Space
cs.IT math.IT
The Grassmannian space $\Gr$ is the set of all $k-$dimensional subspaces of the vector space~\smash{$\F_q^n$}. Recently, codes in the Grassmannian have found an application in network coding. The main goal of this paper is to present efficient enumerative encoding and decoding techniques for the Grassmannian. These coding techniques are based on two different orders for the Grassmannian induced by different representations of $k$-dimensional subspaces of $\F_q^n$. One enumerative coding method is based on a Ferrers diagram representation and on an order for $\Gr$ based on this representation. The complexity of this enumerative coding is $O(k^{5/2} (n-k)^{5/2})$ digit operations. Another order of the Grassmannian is based on a combination of an identifying vector and a reduced row echelon form representation of subspaces. The complexity of the enumerative coding, based on this order, is $O(nk(n-k)\log n\log\log n)$ digits operations. A combination of the two methods reduces the complexity on average by a constant factor.
0911.3262
Moderate-Density Parity-Check Codes
cs.IT math.IT
We propose a new type of short to moderate block-length, linear error-correcting codes, called moderate-density parity-check (MDPC) codes. The number of ones of the parity-check matrix of the codes presented is typically higher than the number of ones of the parity-check matrix of low-density parity-check (LDPC) codes. But, still lower than those of the parity-check matrix of classical block codes. The proposed MDPC codes are cyclic and are designed by constructing idempotents using cyclotomic cosets. The construction is simple and allows finding short block-length, high-rate codes with good minimum distance. Inspired by some recent iterative soft-input soft-output (SISO) decoders used in a context of classical block codes, we propose a low complexity, efficient, iterative decoder called Auto-Diversity (AD) decoder. AD decoder is based on belief propagation (BP) decoder and takes advantage of the fundamental property of automorphism group of the constructed cyclic code.
0911.3280
Automated languages phylogeny from Levenshtein distance
cs.CL q-bio.PE q-bio.QM
Languages evolve over time in a process in which reproduction, mutation and extinction are all possible, similar to what happens to living organisms. Using this similarity it is possible, in principle, to build family trees which show the degree of relatedness between languages. The method used by modern glottochronology, developed by Swadesh in the 1950s, measures distances from the percentage of words with a common historical origin. The weak point of this method is that subjective judgment plays a relevant role. Recently we proposed an automated method that avoids the subjectivity, whose results can be replicated by studies that use the same database and that doesn't require a specific linguistic knowledge. Moreover, the method allows a quick comparison of a large number of languages. We applied our method to the Indo-European and Austronesian families, considering in both cases, fifty different languages. The resulting trees are similar to those of previous studies, but with some important differences in the position of few languages and subgroups. We believe that these differences carry new information on the structure of the tree and on the phylogenetic relationships within families.
0911.3292
Automated words stability and languages phylogeny
cs.CL physics.soc-ph q-bio.PE
The idea of measuring distance between languages seems to have its roots in the work of the French explorer Dumont D'Urville (D'Urville 1832). He collected comparative words lists of various languages during his voyages aboard the Astrolabe from 1826 to1829 and, in his work about the geographical division of the Pacific, he proposed a method to measure the degree of relation among languages. The method used by modern glottochronology, developed by Morris Swadesh in the 1950s (Swadesh 1952), measures distances from the percentage of shared cognates, which are words with a common historical origin. Recently, we proposed a new automated method which uses normalized Levenshtein distance among words with the same meaning and averages on the words contained in a list. Another classical problem in glottochronology is the study of the stability of words corresponding to different meanings. Words, in fact, evolve because of lexical changes, borrowings and replacement at a rate which is not the same for all of them. The speed of lexical evolution is different for different meanings and it is probably related to the frequency of use of the associated words (Pagel et al. 2007). This problem is tackled here by an automated methodology only based on normalized Levenshtein distance.
0911.3298
Understanding the Principles of Recursive Neural networks: A Generative Approach to Tackle Model Complexity
cs.NE cs.LG
Recursive Neural Networks are non-linear adaptive models that are able to learn deep structured information. However, these models have not yet been broadly accepted. This fact is mainly due to its inherent complexity. In particular, not only for being extremely complex information processing models, but also because of a computational expensive learning phase. The most popular training method for these models is back-propagation through the structure. This algorithm has been revealed not to be the most appropriate for structured processing due to problems of convergence, while more sophisticated training methods enhance the speed of convergence at the expense of increasing significantly the computational cost. In this paper, we firstly perform an analysis of the underlying principles behind these models aimed at understanding their computational power. Secondly, we propose an approximate second order stochastic learning algorithm. The proposed algorithm dynamically adapts the learning rate throughout the training phase of the network without incurring excessively expensive computational effort. The algorithm operates in both on-line and batch modes. Furthermore, the resulting learning scheme is robust against the vanishing gradients problem. The advantages of the proposed algorithm are demonstrated with a real-world application example.
0911.3304
Keystroke Dynamics Authentication For Collaborative Systems
cs.LG
We present in this paper a study on the ability and the benefits of using a keystroke dynamics authentication method for collaborative systems. Authentication is a challenging issue in order to guarantee the security of use of collaborative systems during the access control step. Many solutions exist in the state of the art such as the use of one time passwords or smart-cards. We focus in this paper on biometric based solutions that do not necessitate any additional sensor. Keystroke dynamics is an interesting solution as it uses only the keyboard and is invisible for users. Many methods have been published in this field. We make a comparative study of many of them considering the operational constraints of use for collaborative systems.
0911.3318
Re-Pair Compression of Inverted Lists
cs.IR cs.DS
Compression of inverted lists with methods that support fast intersection operations is an active research topic. Most compression schemes rely on encoding differences between consecutive positions with techniques that favor small numbers. In this paper we explore a completely different alternative: We use Re-Pair compression of those differences. While Re-Pair by itself offers fast decompression at arbitrary positions in main and secondary memory, we introduce variants that in addition speed up the operations required for inverted list intersection. We compare the resulting data structures with several recent proposals under various list intersection algorithms, to conclude that our Re-Pair variants offer an interesting time/space tradeoff for this problem, yet further improvements are required for it to improve upon the state of the art.
0911.3347
Optimal strategies for computing symmetric Boolean functions in collocated networks
cs.IT math.IT
We address the problem of finding optimal strategies for computing Boolean symmetric functions. We consider a collocated network, where each node's transmissions can be heard by every other node. Each node has a Boolean measurement and we wish to compute a given Boolean function of these measurements with zero error. We allow for block computation to enhance data fusion efficiency, and determine the minimum worst-case total bits to be communicated to perform the desired computation. We restrict attention to the class of symmetric Boolean functions, which only depend on the number of 1s among the n measurements. We define three classes of functions, namely threshold functions, delta functions and interval functions. We provide exactly optimal strategies for the first two classes, and an order-optimal strategy with optimal preconstant for interval functions. Using these results, we can characterize the complexity of computing percentile type functions, which is of great interest. In our analysis, we use lower bounds from communication complexity theory, and provide an achievable scheme using information theoretic tools.
0911.3349
Seeing Science
astro-ph.IM cs.CV cs.GR stat.AP
The ability to represent scientific data and concepts visually is becoming increasingly important due to the unprecedented exponential growth of computational power during the present digital age. The data sets and simulations scientists in all fields can now create are literally thousands of times as large as those created just 20 years ago. Historically successful methods for data visualization can, and should, be applied to today's huge data sets, but new approaches, also enabled by technology, are needed as well. Increasingly, "modular craftsmanship" will be applied, as relevant functionality from the graphically and technically best tools for a job are combined as-needed, without low-level programming.
0911.3357
Fundamentals of Large Sensor Networks: Connectivity, Capacity, Clocks and Computation
cs.NI cs.IT math.IT
Sensor networks potentially feature large numbers of nodes that can sense their environment over time, communicate with each other over a wireless network, and process information. They differ from data networks in that the network as a whole may be designed for a specific application. We study the theoretical foundations of such large scale sensor networks, addressing four fundamental issues- connectivity, capacity, clocks and function computation. To begin with, a sensor network must be connected so that information can indeed be exchanged between nodes. The connectivity graph of an ad-hoc network is modeled as a random graph and the critical range for asymptotic connectivity is determined, as well as the critical number of neighbors that a node needs to connect to. Next, given connectivity, we address the issue of how much data can be transported over the sensor network. We present fundamental bounds on capacity under several models, as well as architectural implications for how wireless communication should be organized. Temporal information is important both for the applications of sensor networks as well as their operation.We present fundamental bounds on the synchronizability of clocks in networks, and also present and analyze algorithms for clock synchronization. Finally we turn to the issue of gathering relevant information, that sensor networks are designed to do. One needs to study optimal strategies for in-network aggregation of data, in order to reliably compute a composite function of sensor measurements, as well as the complexity of doing so. We address the issue of how such computation can be performed efficiently in a sensor network and the algorithms for doing so, for some classes of functions.
0911.3411
Measuring the Meaning of Words in Contexts: An automated analysis of controversies about Monarch butterflies, Frankenfoods, and stem cells
cs.CL cs.IR physics.soc-ph
Co-words have been considered as carriers of meaning across different domains in studies of science, technology, and society. Words and co-words, however, obtain meaning in sentences, and sentences obtain meaning in their contexts of use. At the science/society interface, words can be expected to have different meanings: the codes of communication that provide meaning to words differ on the varying sides of the interface. Furthermore, meanings and interfaces may change over time. Given this structuring of meaning across interfaces and over time, we distinguish between metaphors and diaphors as reflexive mechanisms that facilitate the translation between contexts. Our empirical focus is on three recent scientific controversies: Monarch butterflies, Frankenfoods, and stem-cell therapies. This study explores new avenues that relate the study of co-word analysis in context with the sociological quest for the analysis and processing of meaning.
0911.3415
Can Scientific Journals be Classified in terms of Aggregated Journal-Journal Citation Relations using the Journal Citation Reports?
cs.DL cs.IR physics.soc-ph
The aggregated citation relations among journals included in the Science Citation Index provide us with a huge matrix which can be analyzed in various ways. Using principal component analysis or factor analysis, the factor scores can be used as indicators of the position of the cited journals in the citing dimensions of the database. Unrotated factor scores are exact, and the extraction of principal components can be made stepwise since the principal components are independent. Rotation may be needed for the designation, but in the rotated solution a model is assumed. This assumption can be legitimated on pragmatic or theoretical grounds. Since the resulting outcomes remain sensitive to the assumptions in the model, an unambiguous classification is no longer possible in this case. However, the factor-analytic solutions allow us to test classifications against the structures contained in the database. This will be demonstrated for the delineation of a set of biochemistry journals.
0911.3416
Classification and Powerlaws: The Logarithmic Transformation
cs.IR cs.DL physics.soc-ph
Logarithmic transformation of the data has been recommended by the literature in the case of highly skewed distributions such as those commonly found in information science. The purpose of the transformation is to make the data conform to the lognormal law of error for inferential purposes. How does this transformation affect the analysis? We factor analyze and visualize the citation environment of the Journal of the American Chemical Society (JACS) before and after a logarithmic transformation. The transformation strongly reduces the variance necessary for classificatory purposes and therefore is counterproductive to the purposes of the descriptive statistics. We recommend against the logarithmic transformation when sets cannot be defined unambiguously. The intellectual organization of the sciences is reflected in the curvilinear parts of the citation distributions, while negative powerlaws fit excellently to the tails of the distributions.
0911.3422
Co-occurrence Matrices and their Applications in Information Science: Extending ACA to the Web Environment
cs.IR cs.DL physics.soc-ph
Co-occurrence matrices, such as co-citation, co-word, and co-link matrices, have been used widely in the information sciences. However, confusion and controversy have hindered the proper statistical analysis of this data. The underlying problem, in our opinion, involved understanding the nature of various types of matrices. This paper discusses the difference between a symmetrical co-citation matrix and an asymmetrical citation matrix as well as the appropriate statistical techniques that can be applied to each of these matrices, respectively. Similarity measures (like the Pearson correlation coefficient or the cosine) should not be applied to the symmetrical co-citation matrix, but can be applied to the asymmetrical citation matrix to derive the proximity matrix. The argument is illustrated with examples. The study then extends the application of co-occurrence matrices to the Web environment where the nature of the available data and thus data collection methods are different from those of traditional databases such as the Science Citation Index. A set of data collected with the Google Scholar search engine is analyzed using both the traditional methods of multivariate analysis and the new visualization software Pajek that is based on social network analysis and graph theory.
0911.3482
Complexity of Networks (reprise)
cs.IT math.IT nlin.AO q-bio.PE
Network or graph structures are ubiquitous in the study of complex systems. Often, we are interested in complexity trends of these system as it evolves under some dynamic. An example might be looking at the complexity of a food web as species enter an ecosystem via migration or speciation, and leave via extinction. In a previous paper, a complexity measure of networks was proposed based on the {\em complexity is information content} paradigm. To apply this paradigm to any object, one must fix two things: a representation language, in which strings of symbols from some alphabet describe, or stand for the objects being considered; and a means of determining when two such descriptions refer to the same object. With these two things set, the information content of an object can be computed in principle from the number of equivalent descriptions describing a particular object. The previously proposed representation language had the deficiency that the fully connected and empty networks were the most complex for a given number of nodes. A variation of this measure, called zcomplexity, applied a compression algorithm to the resulting bitstring representation, to solve this problem. Unfortunately, zcomplexity proved too computationally expensive to be practical. In this paper, I propose a new representation language that encodes the number of links along with the number of nodes and a representation of the linklist. This, like zcomplexity, exhibits minimal complexity for fully connected and empty networks, but is as tractable as the original measure. ...
0911.3514
Sampling and reconstructing signals from a union of linear subspaces
cs.IT math.IT
In this note we study the problem of sampling and reconstructing signals which are assumed to lie on or close to one of several subspaces of a Hilbert space. Importantly, we here consider a very general setting in which we allow infinitely many subspaces in infinite dimensional Hilbert spaces. This general approach allows us to unify many results derived recently in areas such as compressed sensing, affine rank minimisation and analog compressed sensing. Our main contribution is to show that a conceptually simple iterative projection algorithms is able to recover signals from a union of subspaces whenever the sampling operator satisfies a bi-Lipschitz embedding condition. Importantly, this result holds for all Hilbert spaces and unions of subspaces, as long as the sampling procedure satisfies the condition for the set of subspaces considered. In addition to recent results for finite unions of finite dimensional subspaces and infinite unions of subspaces in finite dimensional spaces, we also show that this bi-Lipschitz property can hold in an analog compressed sensing setting in which we have an infinite union of infinite dimensional subspaces living in infinite dimensional space.
0911.3581
X-Learn: An XML-Based, Multi-agent System for Supporting "User-Device" Adaptive E-learning
cs.CY cs.MA
In this paper we present X-Learn, an XML-based, multi-agent system for supporting "user-device" adaptive e-learning. X-Learn is characterized by the following features: (i) it is highly subjective, since it handles quite a rich and detailed user profile that plays a key role during the learning activities; (ii) it is dynamic and flexible, i.e., it is capable of reacting to variations of exigencies and objectives; (iii) it is device-adaptive, since it decides the learning objects to present to the user on the basis of the device she/he is currently exploiting; (iv) it is generic, i.e., it is capable of operating in a large variety of learning contexts; (v) it is XML based, since it exploits many facilities of XML technology for handling and exchanging information connected to e-learning activities. The paper reports also various experimental results as well as a comparison between X-Learn and other related e-learning management systems already presented in the literature.
0911.3600
"Almost automatic" and semantic integration of XML Schemas at various "severity" levels
cs.DB
This paper presents a novel approach for the integration of a set of XML Schemas. The proposed approach is specialized for XML, is almost automatic, semantic and "light". As a further, original, peculiarity, it is parametric w.r.t. a "severity" level against which the integration task is performed. The paper describes the approach in all details, illustrates various theoretical results, presents the experiments we have performed for testing it and, finally, compares it with various related approaches already proposed in the literature.
0911.3633
A Geometric Approach to Sample Compression
cs.LG math.CO math.GT stat.ML
The Sample Compression Conjecture of Littlestone & Warmuth has remained unsolved for over two decades. This paper presents a systematic geometric investigation of the compression of finite maximum concept classes. Simple arrangements of hyperplanes in Hyperbolic space, and Piecewise-Linear hyperplane arrangements, are shown to represent maximum classes, generalizing the corresponding Euclidean result. A main result is that PL arrangements can be swept by a moving hyperplane to unlabeled d-compress any finite maximum class, forming a peeling scheme as conjectured by Kuzmin & Warmuth. A corollary is that some d-maximal classes cannot be embedded into any maximum class of VC dimension d+k, for any constant k. The construction of the PL sweeping involves Pachner moves on the one-inclusion graph, corresponding to moves of a hyperplane across the intersection of d other hyperplanes. This extends the well known Pachner moves for triangulations to cubical complexes.
0911.3643
Multiple Presents: How Search Engines Re-write the Past
cs.IR physics.soc-ph
Internet search engines function in a present which changes continuously. The search engines update their indices regularly, overwriting Web pages with newer ones, adding new pages to the index, and losing older ones. Some search engines can be used to search for information at the internet for specific periods of time. However, these 'date stamps' are not determined by the first occurrence of the pages in the Web, but by the last date at which a page was updated or a new page was added, and the search engine's crawler updated this change in the database. This has major implications for the use of search engines in scholarly research as well as theoretical implications for the conceptions of time and temporality. We examine the interplay between the different updating frequencies by using AltaVista and Google for searches at different moments of time. Both the retrieval of the results and the structure of the retrieved information erodes over time.
0911.3668
Signal acquisition via polarization modulation in single photon sources
quant-ph cs.IT math.IT
A simple model system is introduced for demonstrating how a single photon source might be used to transduce classical analog information. The theoretical scheme results in measurements of analog source samples that are (i) quantized in the sense of analog-to-digital conversion and (ii) corrupted by random noise that is solely due to the quantum uncertainty in detecting the polarization state of each photon. This noise is unavoidable if more than one bit per sample is to be transmitted, and we show how it may be exploited in a manner inspired by suprathreshold stochastic resonance. The system is analyzed information theoretically, as it can be modeled as a noisy optical communication channel, although unlike classical Poisson channels, the detector's photon statistics are binomial. Previous results on binomial channels are adapted to demonstrate numerically that the classical information capacity, and thus the accuracy of the transduction, increases logarithmically with the square root of the number of photons, N. Although the capacity is shown to be reduced when an additional detector nonideality is present, the logarithmic increase with N remains.
0911.3676
Pipelined Encoding for Deterministic and Noisy Relay Networks
cs.IT math.IT
Recent coding strategies for deterministic and noisy relay networks are related to the pipelining of block Markov encoding. For deterministic networks, it is shown that pipelined encoding improves encoding delay, as opposed to end-to-end delay. For noisy networks, it is observed that decode-and-forward exhibits good rate scaling when the signal-to-noise ratio (SNR) increases.
0911.3708
Manipulability of Single Transferable Vote
cs.AI cs.CC cs.GT cs.MA
For many voting rules, it is NP-hard to compute a successful manipulation. However, NP-hardness only bounds the worst-case complexity. Recent theoretical results suggest that manipulation may often be easy in practice. We study empirically the cost of manipulating the single transferable vote (STV) rule. This was one of the first rules shown to be NP-hard to manipulate. It also appears to be one of the harder rules to manipulate since it involves multiple rounds and since, unlike many other rules, it is NP-hard for a single agent to manipulate without weights on the votes or uncertainty about how the other agents have voted. In almost every election in our experiments, it was easy to compute how a single agent could manipulate the election or to prove that manipulation by a single agent was impossible. It remains an interesting open question if manipulation by a coalition of agents is hard to compute in practice.
0911.3717
Artificial Neural Network-based error compensation procedure for low-cost encoders
cs.NE astro-ph.IM physics.comp-ph
An Artificial Neural Network-based error compensation method is proposed for improving the accuracy of resolver-based 16-bit encoders by compensating for their respective systematic error profiles. The error compensation procedure, for a particular encoder, involves obtaining its error profile by calibrating it on a precision rotary table, training the neural network by using a part of this data and then determining the corrected encoder angle by subtracting the ANN-predicted error from the measured value of the encoder angle. Since it is not guaranteed that all the resolvers will have exactly similar error profiles because of the inherent differences in their construction on a micro scale, the ANN has been trained on one error profile at a time and the corresponding weight file is then used only for compensating the systematic error of this particular encoder. The systematic nature of the error profile for each of the encoders has also been validated by repeated calibration of the encoders over a period of time and it was found that the error profiles of a particular encoder recorded at different epochs show near reproducible behavior. The ANN-based error compensation procedure has been implemented for 4 encoders by training the ANN with their respective error profiles and the results indicate that the accuracy of encoders can be improved by nearly an order of magnitude from quoted values of ~6 arc-min to ~0.65 arc-min when their corresponding ANN-generated weight files are used for determining the corrected encoder angle.
0911.3723
Applications of the Dynamic Distance Potential Field Method
cs.MA
Recently the dynamic distance potential field (DDPF) was introduced as a computationally efficient method to make agents in a simulation of pedestrians move rather on the quickest path than the shortest. It can be considered to be an estimated-remaining-journey-time-based one-shot dynamic assignment method for pedestrian route choice on the operational level of dynamics. In this contribution the method is shortly introduced and the effect of the method on RiMEA's test case 11 is investigated.
0911.3753
Evolutionary estimation of a Coupled Markov Chain credit risk model
cs.NE cs.CE
There exists a range of different models for estimating and simulating credit risk transitions to optimally manage credit risk portfolios and products. In this chapter we present a Coupled Markov Chain approach to model rating transitions and thereby default probabilities of companies. As the likelihood of the model turns out to be a non-convex function of the parameters to be estimated, we apply heuristics to find the ML estimators. To this extent, we outline the model and its likelihood function, and present both a Particle Swarm Optimization algorithm, as well as an Evolutionary Optimization algorithm to maximize the likelihood function. Numerical results are shown which suggest a further application of evolutionary optimization techniques for credit risk management.
0911.3823
Google matrix and Ulam networks of intermittency maps
cs.IR cond-mat.dis-nn nlin.AO nlin.CD physics.soc-ph
We study the properties of the Google matrix of an Ulam network generated by intermittency maps. This network is created by the Ulam method which gives a matrix approximant for the Perron-Frobenius operator of dynamical map. The spectral properties of eigenvalues and eigenvectors of this matrix are analyzed. We show that the PageRank of the system is characterized by a power law decay with the exponent $\beta$ dependent on map parameters and the Google damping factor $\alpha$. Under certain conditions the PageRank is completely delocalized so that the Google search in such a situation becomes inefficient.
0911.3842
Musical Genres: Beating to the Rhythms of Different Drums
physics.data-an cs.IR cs.SD physics.soc-ph
Online music databases have increased signicantly as a consequence of the rapid growth of the Internet and digital audio, requiring the development of faster and more efficient tools for music content analysis. Musical genres are widely used to organize music collections. In this paper, the problem of automatic music genre classification is addressed by exploring rhythm-based features obtained from a respective complex network representation. A Markov model is build in order to analyse the temporal sequence of rhythmic notation events. Feature analysis is performed by using two multivariate statistical approaches: principal component analysis(unsupervised) and linear discriminant analysis (supervised). Similarly, two classifiers are applied in order to identify the category of rhythms: parametric Bayesian classifier under gaussian hypothesis (supervised), and agglomerative hierarchical clustering (unsupervised). Qualitative results obtained by Kappa coefficient and the obtained clusters corroborated the effectiveness of the proposed method.
0911.3872
Equivalence perspectives in communication, source-channel connections and universal source-channel separation
cs.IT math.IT
An operational perspective is used to understand the relationship between source and channel coding. This is based on a direct reduction of one problem to another that uses random coding (and hence common randomness) but unlike all prior work, does not involve any functional computations, in particular, no mutual-information computations. This result is then used to prove a universal source-channel separation theorem in the rate-distortion context where universality is in the sense of a compound ``general channel.''
0911.3921
Error Rates of the Maximum-Likelihood Detector for Arbitrary Constellations: Convex/Concave Behavior and Applications
cs.IT math.IT
Motivated by a recent surge of interest in convex optimization techniques, convexity/concavity properties of error rates of the maximum likelihood detector operating in the AWGN channel are studied and extended to frequency-flat slow-fading channels. Generic conditions are identified under which the symbol error rate (SER) is convex/concave for arbitrary multi-dimensional constellations. In particular, the SER is convex in SNR for any one- and two-dimensional constellation, and also in higher dimensions at high SNR. Pairwise error probability and bit error rate are shown to be convex at high SNR, for arbitrary constellations and bit mapping. Universal bounds for the SER 1st and 2nd derivatives are obtained, which hold for arbitrary constellations and are tight for some of them. Applications of the results are discussed, which include optimum power allocation in spatial multiplexing systems, optimum power/time sharing to decrease or increase (jamming problem) error rate, an implication for fading channels ("fading is never good in low dimensions") and optimization of a unitary-precoded OFDM system. For example, the error rate bounds of a unitary-precoded OFDM system with QPSK modulation, which reveal the best and worst precoding, are extended to arbitrary constellations, which may also include coding. The reported results also apply to the interference channel under Gaussian approximation, to the bit error rate when it can be expressed or approximated as a non-negative linear combination of individual symbol error rates, and to coded systems.
0911.3944
Likelihood-based semi-supervised model selection with applications to speech processing
stat.ML cs.CL cs.LG stat.AP
In conventional supervised pattern recognition tasks, model selection is typically accomplished by minimizing the classification error rate on a set of so-called development data, subject to ground-truth labeling by human experts or some other means. In the context of speech processing systems and other large-scale practical applications, however, such labeled development data are typically costly and difficult to obtain. This article proposes an alternative semi-supervised framework for likelihood-based model selection that leverages unlabeled data by using trained classifiers representing each model to automatically generate putative labels. The errors that result from this automatic labeling are shown to be amenable to results from robust statistics, which in turn provide for minimax-optimal censored likelihood ratio tests that recover the nonparametric sign test as a limiting case. This approach is then validated experimentally using a state-of-the-art automatic speech recognition system to select between candidate word pronunciations using unlabeled speech data that only potentially contain instances of the words under test. Results provide supporting evidence for the utility of this approach, and suggest that it may also find use in other applications of machine learning.
0911.3979
Making the road by searching - A search engine based on Swarm Information Foraging
cs.IR cs.HC
Search engines are nowadays one of the most important entry points for Internet users and a central tool to solve most of their information needs. Still, there exist a substantial amount of users' searches which obtain unsatisfactory results. Needless to say, several lines of research aim to increase the relevancy of the results users retrieve. In this paper the authors frame this problem within the much broader (and older) one of information overload. They argue that users' dissatisfaction with search engines is a currently common manifestation of such a problem, and propose a different angle from which to tackle with it. As it will be discussed, their approach shares goals with a current hot research topic (namely, learning to rank for information retrieval) but, unlike the techniques commonly applied in that field, their technique cannot be exactly considered machine learning and, additionally, it can be used to change the search engine's response in real-time, driven by the users behavior. Their proposal adapts concepts from Swarm Intelligence (in particular, Ant Algorithms) from an Information Foraging point of view. It will be shown that the technique is not only feasible, but also an elegant solution to the stated problem; what's more, it achieves promising results, both increasing the performance of a major search engine for informational queries, and substantially reducing the time users require to answer complex information needs.
0911.3992
Storage Coding for Wear Leveling in Flash Memories
cs.IT math.IT
Flash memory is a non-volatile computer memory comprised of blocks of cells, wherein each cell is implemented as either NAND or NOR floating gate. NAND flash is currently the most widely used type of flash memory. In a NAND flash memory, every block of cells consists of numerous pages; rewriting even a single page requires the whole block to be erased and reprogrammed. Block erasures determine both the longevity and the efficiency of a flash memory. Therefore, when data in a NAND flash memory are reorganized, minimizing the total number of block erasures required to achieve the desired data movement is an important goal. This leads to the flash data movement problem studied in this paper. We show that coding can significantly reduce the number of block erasures required for data movement, and present several optimal or nearly optimal data-movement algorithms based upon ideas from coding theory and combinatorics. In particular, we show that the sorting-based (non-coding) schemes require at least O(nlogn) erasures to move data among n blocks, whereas coding-based schemes require only O(n) erasures. Furthermore, coding-based schemes use only one auxiliary block, which is the best possible, and achieve a good balance between the number of erasures in each of the n+1 blocks.
0911.4046
Super-Linear Convergence of Dual Augmented-Lagrangian Algorithm for Sparsity Regularized Estimation
stat.ML cs.LG stat.ME
We analyze the convergence behaviour of a recently proposed algorithm for regularized estimation called Dual Augmented Lagrangian (DAL). Our analysis is based on a new interpretation of DAL as a proximal minimization algorithm. We theoretically show under some conditions that DAL converges super-linearly in a non-asymptotic and global sense. Due to a special modelling of sparse estimation problems in the context of machine learning, the assumptions we make are milder and more natural than those made in conventional analysis of augmented Lagrangian algorithms. In addition, the new interpretation enables us to generalize DAL to wide varieties of sparse estimation problems. We experimentally confirm our analysis in a large scale $\ell_1$-regularized logistic regression problem and extensively compare the efficiency of DAL algorithm to previously proposed algorithms on both synthetic and benchmark datasets.
0911.4167
Wyner-Ziv Coding over Broadcast Channels: Digital Schemes
cs.IT math.IT
This paper addresses lossy transmission of a common source over a broadcast channel when there is correlated side information at the receivers, with emphasis on the quadratic Gaussian and binary Hamming cases. A digital scheme that combines ideas from the lossless version of the problem, i.e., Slepian-Wolf coding over broadcast channels, and dirty paper coding, is presented and analyzed. This scheme uses layered coding where the common layer information is intended for both receivers and the refinement information is destined only for one receiver. For the quadratic Gaussian case, a quantity characterizing the overall quality of each receiver is identified in terms of channel and side information parameters. It is shown that it is more advantageous to send the refinement information to the receiver with "better" overall quality. In the case where all receivers have the same overall quality, the presented scheme becomes optimal. Unlike its lossless counterpart, however, the problem eludes a complete characterization.
0911.4178
Folksonomic Tag Clouds as an Aid to Content Indexing
cs.IR cs.HC
Social tagging systems have recently developed as a popular method of data organisation on the Internet. These systems allow users to organise their content in a way that makes sense to them, rather than forcing them to use a pre-determined and rigid set of categorisations. These folksonomies provide well populated sources of unstructured tags describing web resources which could potentially be used as semantic index terms for these resources. However getting people to agree on what tags best describe a resource is a difficult problem, therefore any feature which increases the consistency and stability of terms chosen would be extremely beneficial. We investigate how the provision of a tag cloud, a weighted list of terms commonly used to assist in browsing a folksonomy, during the tagging process itself influences the tags produced and how difficult the user perceived the task to be. We show that illustrating the most popular tags to users assists in the tagging process and encourages a stable and consistent folksonomy to form.
0911.4207
An information theoretic approach to statistical dependence: copula information
q-fin.ST cs.IT math.IT physics.data-an stat.AP
We discuss the connection between information and copula theories by showing that a copula can be employed to decompose the information content of a multivariate distribution into marginal and dependence components, with the latter quantified by the mutual information. We define the information excess as a measure of deviation from a maximum entropy distribution. The idea of marginal invariant dependence measures is also discussed and used to show that empirical linear correlation underestimates the amplitude of the actual correlation in the case of non-Gaussian marginals. The mutual information is shown to provide an upper bound for the asymptotic empirical log-likelihood of a copula. An analytical expression for the information excess of T-copulas is provided, allowing for simple model identification within this family. We illustrate the framework in a financial data set.
0911.4219
Message Passing Algorithms for Compressed Sensing: I. Motivation and Construction
cs.IT math.IT
In a recent paper, the authors proposed a new class of low-complexity iterative thresholding algorithms for reconstructing sparse signals from a small set of linear measurements \cite{DMM}. The new algorithms are broadly referred to as AMP, for approximate message passing. This is the first of two conference papers describing the derivation of these algorithms, connection with the related literature, extensions of the original framework, and new empirical evidence. In particular, the present paper outlines the derivation of AMP from standard sum-product belief propagation, and its extension in several directions. We also discuss relations with formal calculations based on statistical mechanics methods.
0911.4222
Message Passing Algorithms for Compressed Sensing: II. Analysis and Validation
cs.IT math.IT
In a recent paper, the authors proposed a new class of low-complexity iterative thresholding algorithms for reconstructing sparse signals from a small set of linear measurements \cite{DMM}. The new algorithms are broadly referred to as AMP, for approximate message passing. This is the second of two conference papers describing the derivation of these algorithms, connection with related literature, extensions of original framework, and new empirical evidence. This paper describes the state evolution formalism for analyzing these algorithms, and some of the conclusions that can be drawn from this formalism. We carried out extensive numerical simulations to confirm these predictions. We present here a few representative results.
0911.4230
Introduction to Bioinformatics
cs.CE
Bioinformatics is a new discipline that addresses the need to manage and interpret the data that in the past decade was massively generated by genomic research. This discipline represents the convergence of genomics, biotechnology and information technology, and encompasses analysis and interpretation of data, modeling of biological phenomena, and development of algorithms and statistics. This article presents an introduction to bioinformatics
0911.4262
Towards Industrialized Conception and Production of Serious Games
cs.LG cs.HC
Serious Games (SGs) have experienced a tremendous outburst these last years. Video game companies have been producing fun, user-friendly SGs, but their educational value has yet to be proven. Meanwhile, cognition research scientist have been developing SGs in such a way as to guarantee an educational gain, but the fun and attractive characteristics featured often would not meet the public's expectations. The ideal SG must combine these two aspects while still being economically viable. In this article, we propose a production chain model to efficiently conceive and produce SGs that are certified for their educational gain and fun qualities. Each step of this chain will be described along with the human actors, the tools and the documents that intervene.
0911.4292
Similarity Measures, Author Cocitation Analysis, and Information Theory
cs.IR physics.soc-ph
The use of Pearson's correlation coefficient in Author Cocitation Analysis was compared with Salton's cosine measure in a number of recent contributions. Unlike the Pearson correlation, the cosine is insensitive to the number of zeros. However, one has the option of applying a logarithmic transformation in correlation analysis. Information calculus is based on both the logarithmic transformation and provides a non-parametric statistics. Using this methodology one can cluster a document set in a precise way and express the differences in terms of bits of information. The algorithm is explained and used on the data set which was made the subject of this discussion.
0911.4302
An Indicator of Research Front Activity: Measuring Intellectual Organization as Uncertainty Reduction in Document Sets
cs.DL cs.IR physics.soc-ph
When using scientific literature to model scholarly discourse, a research specialty can be operationalized as an evolving set of related documents. Each publication can be expected to contribute to the further development of the specialty at the research front. The specific combinations of title words and cited references in a paper can then be considered as a signature of the knowledge claim in the paper: new words and combinations of words can be expected to represent variation, while each paper is at the same time selectively positioned into the intellectual organization of a field using context-relevant references. Can the mutual information among these three dimensions--title words, cited references, and sequence numbers--be used as an indicator of the extent to which intellectual organization structures the uncertainty prevailing at a research front? The effect of the discovery of nanotubes (1991) on the previously existing field of fullerenes is used as a test case. Thereafter, this method is applied to science studies with a focus on scientometrics using various sample delineations. An emerging research front about citation analysis can be indicated.
0911.4329
Structural Consistency: Enabling XML Keyword Search to Eliminate Spurious Results Consistently
cs.DB
XML keyword search is a user-friendly way to query XML data using only keywords. In XML keyword search, to achieve high precision without sacrificing recall, it is important to remove spurious results not intended by the user. Efforts to eliminate spurious results have enjoyed some success by using the concepts of LCA or its variants, SLCA and MLCA. However, existing methods still could find many spurious results. The fundamental cause for the occurrence of spurious results is that the existing methods try to eliminate spurious results locally without global examination of all the query results and, accordingly, some spurious results are not consistently eliminated. In this paper, we propose a novel keyword search method that removes spurious results consistently by exploiting the new concept of structural consistency.
0911.4385
Bio-inspired speed detection and discrimination
cs.CV cs.NE
In the field of computer vision, a crucial task is the detection of motion (also called optical flow extraction). This operation allows analysis such as 3D reconstruction, feature tracking, time-to-collision and novelty detection among others. Most of the optical flow extraction techniques work within a finite range of speeds. Usually, the range of detection is extended towards higher speeds by combining some multiscale information in a serial architecture. This serial multi-scale approach suffers from the problem of error propagation related to the number of scales used in the algorithm. On the other hand, biological experiments show that human motion perception seems to follow a parallel multiscale scheme. In this work we present a bio-inspired parallel architecture to perform detection of motion, providing a wide range of operation and avoiding error propagation associated with the serial architecture. To test our algorithm, we perform relative error comparisons between both classical and proposed techniques, showing that the parallel architecture is able to achieve motion detection with results similar to the serial approach.