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cs/0501052
Stochastic Differential Games in a Non-Markovian Setting
cs.IT cs.CE math.IT
Stochastic differential games are considered in a non-Markovian setting. Typically, in stochastic differential games the modulating process of the diffusion equation describing the state flow is taken to be Markovian. Then Nash equilibria or other types of solution such as Pareto equilibria are constructed using Hamilton-Jacobi-Bellman (HJB) equations. But in a non-Markovian setting the HJB method is not applicable. To examine the non-Markovian case, this paper considers the situation in which the modulating process is a fractional Brownian motion. Fractional noise calculus is used for such models to find the Nash equilibria explicitly. Although fractional Brownian motion is taken as the modulating process because of its versatility in modeling in the fields of finance and networks, the approach in this paper has the merit of being applicable to more general Gaussian stochastic differential games with only slight conceptual modifications. This work has applications in finance to stock price modeling which incorporates the effect of institutional investors, and to stochastic differential portfolio games in markets in which the stock prices follow diffusions modulated with fractional Brownian motion.
cs/0501053
Relational Algebra as non-Distributive Lattice
cs.DB
We reduce the set of classic relational algebra operators to two binary operations: natural join and generalized union. We further demonstrate that this set of operators is relationally complete and honors lattice axioms.
cs/0501054
Arbitrage in Fractal Modulated Markets When the Volatility is Stochastic
cs.IT cs.CE math.IT
In this paper an arbitrage strategy is constructed for the modified Black-Scholes model driven by fractional Brownian motion or by a time changed fractional Brownian motion, when the volatility is stochastic. This latter property allows the heavy tailedness of the log returns of the stock prices to be also accounted for in addition to the long range dependence introduced by the fractional Brownian motion. Work has been done previously on this problem for the case with constant `volatility' and without a time change; here these results are extended to the case of stochastic volatility models when the modulator is fractional Brownian motion or a time change of it. (Volatility in fractional Black-Scholes models does not carry the same meaning as in the classic Black-Scholes framework, which is made clear in the text.) Since fractional Brownian motion is not a semi-martingale, the Black-Scholes differential equation is not well-defined sense for arbitrary predictable volatility processes. However, it is shown here that any almost surely continuous and adapted process having zero quadratic variation can act as an integrator over functions of the integrator and over the family of continuous adapted semi-martingales. Moreover it is shown that the integral also has zero quadratic variation, and therefore that the integral itself can be an integrator. This property of the integral is crucial in developing the arbitrage strategy. Since fractional Brownian motion and a time change of fractional Brownian motion have zero quadratic variation, these results are applicable to these cases in particular. The appropriateness of fractional Brownian motion as a means of modeling stock price returns is discussed as well.
cs/0501055
Consistency Problems for Jump-Diffusion Models
cs.IT cs.CE math.IT
In this paper consistency problems for multi-factor jump-diffusion models, where the jump parts follow multivariate point processes are examined. First the gap between jump-diffusion models and generalized Heath-Jarrow-Morton (HJM) models is bridged. By applying the drift condition for a generalized arbitrage-free HJM model, the consistency condition for jump-diffusion models is derived. Then we consider a case in which the forward rate curve has a separable structure, and obtain a specific version of the general consistency condition. In particular, a necessary and sufficient condition for a jump-diffusion model to be affine is provided. Finally the Nelson-Siegel type of forward curve structures is discussed. It is demonstrated that under regularity condition, there exists no jump-diffusion model consistent with the Nelson-Siegel curves.
cs/0501056
A Large Deviations Approach to Sensor Scheduling for Detection of Correlated Random Fields
cs.IT math.IT
The problem of scheduling sensor transmissions for the detection of correlated random fields using spatially deployed sensors is considered. Using the large deviations principle, a closed-form expression for the error exponent of the miss probability is given as a function of the sensor spacing and signal-to-noise ratio (SNR). It is shown that the error exponent has a distinct characteristic: at high SNR, the error exponent is monotonically increasing with respect to sensor spacing, while at low SNR there is an optimal spacing for scheduled sensors.
cs/0501057
Concavity of the auxiliary function appearing in quantum reliability function an classical-quantum channels
cs.IT math.IT
Concavity of the auxiliary function which appears in the random coding exponent as the lower bound of the quantum reliability function for general quantum states is proven for s between 0 and 1.
cs/0501058
Estimation of the Number of Sources in Unbalanced Arrays via Information Theoretic Criteria
cs.IT math.IT
Estimating the number of sources impinging on an array of sensors is a well known and well investigated problem. A common approach for solving this problem is to use an information theoretic criterion, such as Minimum Description Length (MDL) or the Akaike Information Criterion (AIC). The MDL estimator is known to be a consistent estimator, robust against deviations from the Gaussian assumption, and non-robust against deviations from the point source and/or temporally or spatially white additive noise assumptions. Over the years several alternative estimation algorithms have been proposed and tested. Usually, these algorithms are shown, using computer simulations, to have improved performance over the MDL estimator, and to be robust against deviations from the assumed spatial model. Nevertheless, these robust algorithms have high computational complexity, requiring several multi-dimensional searches. In this paper, motivated by real life problems, a systematic approach toward the problem of robust estimation of the number of sources using information theoretic criteria is taken. An MDL type estimator that is robust against deviation from assumption of equal noise level across the array is studied. The consistency of this estimator, even when deviations from the equal noise level assumption occur, is proven. A novel low-complexity implementation method avoiding the need for multi-dimensional searches is presented as well, making this estimator a favorable choice for practical applications.
cs/0501061
Optimal and Suboptimal Finger Selection Algorithms for MMSE Rake Receivers in Impulse Radio Ultra-Wideband Systems
cs.IT math.IT
Convex relaxations of the optimal finger selection algorithm are proposed for a minimum mean square error (MMSE) Rake receiver in an impulse radio ultra-wideband system. First, the optimal finger selection problem is formulated as an integer programming problem with a non-convex objective function. Then, the objective function is approximated by a convex function and the integer programming problem is solved by means of constraint relaxation techniques. The proposed algorithms are suboptimal due to the approximate objective function and the constraint relaxation steps. However, they can be used in conjunction with the conventional finger selection algorithm, which is suboptimal on its own since it ignores the correlation between multipath components, to obtain performances reasonably close to that of the optimal scheme that cannot be implemented in practice due to its complexity. The proposed algorithms leverage convexity of the optimization problem formulations, which is the watershed between `easy' and `difficult' optimization problems.
cs/0501062
On The Tradeoff Between Two Types of Processing Gain
cs.IT math.IT
One of the features characterizing almost every multiple access (MA) communication system is the processing gain. Through the use of spreading sequences, the processing gain of Random CDMA systems (RCDMA), is devoted to both bandwidth expansion and orthogonalization of the signals transmitted by different users. Another type of multiple access system is Impulse Radio (IR). In many aspects, IR systems are similar to time division multiple access (TDMA) systems, and the processing gain of IR systems represents the ratio between the actual transmission time and the total time between two consecutive ransmissions (on-plus-off to on ratio). While CDMA systems, which constantly excite the channel, rely on spreading sequences to orthogonalize the signals transmitted by different users, IR systems transmit a series of short pulses and the orthogonalization between the signals transmitted by different users is achieved by the fact that most of the pulses do not collide with each other at the receiver. In this paper, a general class of MA communication systems that use both types of processing gain is presented, and both IR and RCDMA systems are demonstrated to be two special cases of this more general class of systems. The bit error rate (BER) of several receivers as a function of the ratio between the two types of processing gain is analyzed and compared under the constraint that the total processing gain of the system is large and fixed. It is demonstrated that in non inter-symbol interference (ISI) channels there is no tradeoff between the two types of processing gain. However, in ISI channels a tradeoff between the two types of processing gain exists. In addition, the sub-optimality of RCDMA systems in frequency selective channels is established.
cs/0501063
Bandit Problems with Side Observations
cs.IT cs.LG math.IT
An extension of the traditional two-armed bandit problem is considered, in which the decision maker has access to some side information before deciding which arm to pull. At each time t, before making a selection, the decision maker is able to observe a random variable X_t that provides some information on the rewards to be obtained. The focus is on finding uniformly good rules (that minimize the growth rate of the inferior sampling time) and on quantifying how much the additional information helps. Various settings are considered and for each setting, lower bounds on the achievable inferior sampling time are developed and asymptotically optimal adaptive schemes achieving these lower bounds are constructed.
cs/0501064
A Non-Cooperative Power Control Game for Multi-Carrier CDMA Systems
cs.IT math.IT
In this work, a non-cooperative power control game for multi-carrier CDMA systems is proposed. In the proposed game, each user needs to decide how much power to transmit over each carrier to maximize its overall utility. The utility function considered here measures the number of reliable bits transmitted per joule of energy consumed. It is shown that the user's utility is maximized when the user transmits only on the carrier with the best "effective channel". The existence and uniqueness of Nash equilibrium for the proposed game are investigated and the properties of equilibrium are studied. Also, an iterative and distributed algorithm for reaching the equilibrium (if it exists) is presented. It is shown that the proposed approach results in a significant improvement in the total utility achieved at equilibrium compared to the case in which each user maximizes its utility over each carrier independently.
cs/0501066
The Noncoherent Rician Fading Channel -- Part I : Structure of the Capacity-Achieving Input
cs.IT math.IT
Transmission of information over a discrete-time memoryless Rician fading channel is considered where neither the receiver nor the transmitter knows the fading coefficients. First the structure of the capacity-achieving input signals is investigated when the input is constrained to have limited peakedness by imposing either a fourth moment or a peak constraint. When the input is subject to second and fourth moment limitations, it is shown that the capacity-achieving input amplitude distribution is discrete with a finite number of mass points in the low-power regime. A similar discrete structure for the optimal amplitude is proven over the entire SNR range when there is only a peak power constraint. The Rician fading with phase-noise channel model, where there is phase uncertainty in the specular component, is analyzed. For this model it is shown that, with only an average power constraint, the capacity-achieving input amplitude is discrete with a finite number of levels. For the classical average power limited Rician fading channel, it is proven that the optimal input amplitude distribution has bounded support.
cs/0501067
The Noncoherent Rician Fading Channel -- Part II : Spectral Efficiency in the Low-Power Regime
cs.IT math.IT
Transmission of information over a discrete-time memoryless Rician fading channel is considered where neither the receiver nor the transmitter knows the fading coefficients. The spectral-efficiency/bit-energy tradeoff in the low-power regime is examined when the input has limited peakedness. It is shown that if a fourth moment input constraint is imposed or the input peak-to-average power ratio is limited, then in contrast to the behavior observed in average power limited channels, the minimum bit energy is not always achieved at zero spectral efficiency. The low-power performance is also characterized when there is a fixed peak limit that does not vary with the average power. A new signaling scheme that overlays phase-shift keying on on-off keying is proposed and shown to be optimally efficient in the low-power regime.
cs/0501068
Learning to automatically detect features for mobile robots using second-order Hidden Markov Models
cs.AI
In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, especially in speech recognition. Their main advantages over other methods (such as neural networks) are their ability to model noisy temporal signals of variable length. We show in this paper that this approach is well suited for interpretation of temporal sequences of mobile-robot sensor data. We present two distinct experiments and results: the first one in an indoor environment where a mobile robot learns to detect features like open doors or T-intersections, the second one in an outdoor environment where a different mobile robot has to identify situations like climbing a hill or crossing a rock.
cs/0501071
Capacity Regions and Optimal Power Allocation for Groupwise Multiuser Detection
cs.IT math.IT
In this paper, optimal power allocation and capacity regions are derived for GSIC (groupwise successive interference cancellation) systems operating in multipath fading channels, under imperfect channel estimation conditions. It is shown that the impact of channel estimation errors on the system capacity is two-fold: it affects the receivers' performance within a group of users, as well as the cancellation performance (through cancellation errors). An iterative power allocation algorithm is derived, based on which it can be shown that the total required received power is minimized when the groups are ordered according to their cancellation errors, and the first detected group has the smallest cancellation error. Performace/complexity tradeoff issues are also discussed by directly comparing the system capacity for different implementations: GSIC with linear minimum-mean-square error (LMMSE) receivers within the detection groups, GSIC with matched filter receivers, multicode LMMSE systems, and simple all matched filter receivers systems.
cs/0501072
Inferring knowledge from a large semantic network
cs.AI
In this paper, we present a rich semantic network based on a differential analysis. We then detail implemented measures that take into account common and differential features between words. In a last section, we describe some industrial applications.
cs/0501077
Ontology-Based Users & Requests Clustering in Customer Service Management System
cs.IR cs.CL
Customer Service Management is one of major business activities to better serve company customers through the introduction of reliable processes and procedures. Today this kind of activities is implemented through e-services to directly involve customers into business processes. Traditionally Customer Service Management involves application of data mining techniques to discover usage patterns from the company knowledge memory. Hence grouping of customers/requests to clusters is one of major technique to improve the level of company customization. The goal of this paper is to present an efficient for implementation approach for clustering users and their requests. The approach uses ontology as knowledge representation model to improve the semantic interoperability between units of the company and customers. Some fragments of the approach tested in an industrial company are also presented in the paper.
cs/0501078
Multi-document Biography Summarization
cs.CL
In this paper we describe a biography summarization system using sentence classification and ideas from information retrieval. Although the individual techniques are not new, assembling and applying them to generate multi-document biographies is new. Our system was evaluated in DUC2004. It is among the top performers in task 5-short summaries focused by person questions.
cs/0501079
Data Mining for Actionable Knowledge: A Survey
cs.DB cs.AI
The data mining process consists of a series of steps ranging from data cleaning, data selection and transformation, to pattern evaluation and visualization. One of the central problems in data mining is to make the mined patterns or knowledge actionable. Here, the term actionable refers to the mined patterns suggest concrete and profitable actions to the decision-maker. That is, the user can do something to bring direct benefits (increase in profits, reduction in cost, improvement in efficiency, etc.) to the organization's advantage. However, there has been written no comprehensive survey available on this topic. The goal of this paper is to fill the void. In this paper, we first present two frameworks for mining actionable knowledge that are inexplicitly adopted by existing research methods. Then we try to situate some of the research on this topic from two different viewpoints: 1) data mining tasks and 2) adopted framework. Finally, we specify issues that are either not addressed or insufficiently studied yet and conclude the paper.
cs/0501081
A Tree Search Method for Iterative Decoding of Underdetermined Multiuser Systems
cs.IT math.IT
Application of the turbo principle to multiuser decoding results in an exchange of probability distributions between two sets of constraints. Firstly, constraints imposed by the multiple-access channel, and secondly, individual constraints imposed by each users' error control code. A-posteriori probability computation for the first set of constraints is prohibitively complex for all but a small number of users. Several lower complexity approaches have been proposed in the literature. One class of methods is based on linear filtering (e.g. LMMSE). A more recent approach is to compute approximations to the posterior probabilities by marginalising over a subset of sequences (list detection). Most of the list detection methods are restricted to non-singular systems. In this paper, we introduce a transformation that permits application of standard tree-search methods to underdetermined systems. We find that the resulting tree-search based receiver outperforms existing methods.
cs/0501082
A Group-Theoretic Approach to the WSSUS Pulse Design Problem
cs.IT math.IT
We consider the pulse design problem in multicarrier transmission where the pulse shapes are adapted to the second order statistics of the WSSUS channel. Even though the problem has been addressed by many authors analytical insights are rather limited. First we show that the problem is equivalent to the pure state channel fidelity in quantum information theory. Next we present a new approach where the original optimization functional is related to an eigenvalue problem for a pseudo differential operator by utilizing unitary representations of the Weyl--Heisenberg group.A local approximation of the operator for underspread channels is derived which implicitly covers the concepts of pulse scaling and optimal phase space displacement. The problem is reformulated as a differential equation and the optimal pulses occur as eigenstates of the harmonic oscillator Hamiltonian. Furthermore this operator--algebraic approach is extended to provide exact solutions for different classes of scattering environments.
cs/0501084
Towards Automated Integration of Guess and Check Programs in Answer Set Programming: A Meta-Interpreter and Applications
cs.AI
Answer set programming (ASP) with disjunction offers a powerful tool for declaratively representing and solving hard problems. Many NP-complete problems can be encoded in the answer set semantics of logic programs in a very concise and intuitive way, where the encoding reflects the typical "guess and check" nature of NP problems: The property is encoded in a way such that polynomial size certificates for it correspond to stable models of a program. However, the problem-solving capacity of full disjunctive logic programs (DLPs) is beyond NP, and captures a class of problems at the second level of the polynomial hierarchy. While these problems also have a clear "guess and check" structure, finding an encoding in a DLP reflecting this structure may sometimes be a non-obvious task, in particular if the "check" itself is a coNP-complete problem; usually, such problems are solved by interleaving separate guess and check programs, where the check is expressed by inconsistency of the check program. In this paper, we present general transformations of head-cycle free (extended) disjunctive logic programs into stratified and positive (extended) disjunctive logic programs based on meta-interpretation techniques. The answer sets of the original and the transformed program are in simple correspondence, and, moreover, inconsistency of the original program is indicated by a designated answer set of the transformed program. Our transformations facilitate the integration of separate "guess" and "check" programs, which are often easy to obtain, automatically into a single disjunctive logic program. Our results complement recent results on meta-interpretation in ASP, and extend methods and techniques for a declarative "guess and check" problem solving paradigm through ASP.
cs/0501085
Space Frequency Codes from Spherical Codes
cs.IT math.IT
A new design method for high rate, fully diverse ('spherical') space frequency codes for MIMO-OFDM systems is proposed, which works for arbitrary numbers of antennas and subcarriers. The construction exploits a differential geometric connection between spherical codes and space time codes. The former are well studied e.g. in the context of optimal sequence design in CDMA systems, while the latter serve as basic building blocks for space frequency codes. In addition a decoding algorithm with moderate complexity is presented. This is achieved by a lattice based construction of spherical codes, which permits lattice decoding algorithms and thus offers a substantial reduction of complexity.
cs/0501086
Clever Search: A WordNet Based Wrapper for Internet Search Engines
cs.AI
This paper presents an approach to enhance search engines with information about word senses available in WordNet. The approach exploits information about the conceptual relations within the lexical-semantic net. In the wrapper for search engines presented, WordNet information is used to specify user's request or to classify the results of a publicly available web search engine, like google, yahoo, etc.
cs/0501088
Information estimations and analysis of structures
cs.IT math.IT
In this paper have written the results of the information analysis of structures. The obtained information estimation (IE) are based on an entropy measure of C. Shannon. Obtained IE is univalent both for the non-isomorphic and for the isomorphic graphs, algorithmically, it is asymptotically steady and has vector character. IE can be used for the solution of the problems ranking of structures by the preference, the evaluation of the structurization of subject area, the solution of the problems of structural optimization. Information estimations and method of the information analysis of structures it can be used in many fields of knowledge (Electrical Systems and Circuit, Image recognition, Computer technology, Databases and Bases of knowledge, Organic chemistry, Biology and others) and it can be base for the structure calculus.
cs/0501089
Issues in Exploiting GermaNet as a Resource in Real Applications
cs.AI
This paper reports about experiments with GermaNet as a resource within domain specific document analysis. The main question to be answered is: How is the coverage of GermaNet in a specific domain? We report about results of a field test of GermaNet for analyses of autopsy protocols and present a sketch about the integration of GermaNet inside XDOC. Our remarks will contribute to a GermaNet user's wish list.
cs/0501090
Stochastic Iterative Decoders
cs.IT math.IT
This paper presents a stochastic algorithm for iterative error control decoding. We show that the stochastic decoding algorithm is an approximation of the sum-product algorithm. When the code's factor graph is a tree, as with trellises, the algorithm approaches maximum a-posteriori decoding. We also demonstrate a stochastic approximations to the alternative update rule known as successive relaxation. Stochastic decoders have very simple digital implementations which have almost no RAM requirements. We present example stochastic decoders for a trellis-based Hamming code, and for a Block Turbo code constructed from Hamming codes.
cs/0501091
A complexity-regularized quantization approach to nonlinear dimensionality reduction
cs.IT math.IT
We consider the problem of nonlinear dimensionality reduction: given a training set of high-dimensional data whose ``intrinsic'' low dimension is assumed known, find a feature extraction map to low-dimensional space, a reconstruction map back to high-dimensional space, and a geometric description of the dimension-reduced data as a smooth manifold. We introduce a complexity-regularized quantization approach for fitting a Gaussian mixture model to the training set via a Lloyd algorithm. Complexity regularization controls the trade-off between adaptation to the local shape of the underlying manifold and global geometric consistency. The resulting mixture model is used to design the feature extraction and reconstruction maps and to define a Riemannian metric on the low-dimensional data. We also sketch a proof of consistency of our scheme for the purposes of estimating the unknown underlying pdf of high-dimensional data.
cs/0501092
Multi-Vehicle Cooperative Control Using Mixed Integer Linear Programming
cs.RO cs.AI cs.MA
We present methods to synthesize cooperative strategies for multi-vehicle control problems using mixed integer linear programming. Complex multi-vehicle control problems are expressed as mixed logical dynamical systems. Optimal strategies for these systems are then solved for using mixed integer linear programming. We motivate the methods on problems derived from an adversarial game between two teams of robots called RoboFlag. We assume the strategy for one team is fixed and governed by state machines. The strategy for the other team is generated using our methods. Finally, we perform an average case computational complexity study on our approach.
cs/0501093
Transforming Business Rules Into Natural Language Text
cs.AI
The aim of the project presented in this paper is to design a system for an NLG architecture, which supports the documentation process of eBusiness models. A major task is to enrich the formal description of an eBusiness model with additional information needed in an NLG task.
cs/0501094
Corpus based Enrichment of GermaNet Verb Frames
cs.AI
Lexical semantic resources, like WordNet, are often used in real applications of natural language document processing. For example, we integrated GermaNet in our document suite XDOC of processing of German forensic autopsy protocols. In addition to the hypernymy and synonymy relation, we want to adapt GermaNet's verb frames for our analysis. In this paper we outline an approach for the domain related enrichment of GermaNet verb frames by corpus based syntactic and co-occurred data analyses of real documents.
cs/0501095
Context Related Derivation of Word Senses
cs.AI
Real applications of natural language document processing are very often confronted with domain specific lexical gaps during the analysis of documents of a new domain. This paper describes an approach for the derivation of domain specific concepts for the extension of an existing ontology. As resources we need an initial ontology and a partially processed corpus of a domain. We exploit the specific characteristic of the sublanguage in the corpus. Our approach is based on syntactical structures (noun phrases) and compound analyses to extract information required for the extension of GermaNet's lexical resources.
cs/0501096
Transforming and Enriching Documents for the Semantic Web
cs.AI
We suggest to employ techniques from Natural Language Processing (NLP) and Knowledge Representation (KR) to transform existing documents into documents amenable for the Semantic Web. Semantic Web documents have at least part of their semantics and pragmatics marked up explicitly in both a machine processable as well as human readable manner. XML and its related standards (XSLT, RDF, Topic Maps etc.) are the unifying platform for the tools and methodologies developed for different application scenarios.
cs/0502001
Some Extensions of Gallager's Method to General Sources and Channels
cs.IT math.IT
The Gallager bound is well known in the area of channel coding. However, most discussions about it mainly focus on its applications to memoryless channels. We show in this paper that the bounds obtained by Gallager's method are very tight even for general sources and channels that are defined in the information-spectrum theory. Our method is mainly based on the estimations of error exponents in those bounds, and by these estimations we proved the direct part of the Slepian-Wolf theorem and channel coding theorem for general sources and channels.
cs/0502004
Asymptotic Log-loss of Prequential Maximum Likelihood Codes
cs.LG cs.IT math.IT
We analyze the Dawid-Rissanen prequential maximum likelihood codes relative to one-parameter exponential family models M. If data are i.i.d. according to an (essentially) arbitrary P, then the redundancy grows at rate c/2 ln n. We show that c=v1/v2, where v1 is the variance of P, and v2 is the variance of the distribution m* in M that is closest to P in KL divergence. This shows that prequential codes behave quite differently from other important universal codes such as the 2-part MDL, Shtarkov and Bayes codes, for which c=1. This behavior is undesirable in an MDL model selection setting.
cs/0502006
Neural network ensembles: Evaluation of aggregation algorithms
cs.AI cs.NE
Ensembles of artificial neural networks show improved generalization capabilities that outperform those of single networks. However, for aggregation to be effective, the individual networks must be as accurate and diverse as possible. An important problem is, then, how to tune the aggregate members in order to have an optimal compromise between these two conflicting conditions. We present here an extensive evaluation of several algorithms for ensemble construction, including new proposals and comparing them with standard methods in the literature. We also discuss a potential problem with sequential aggregation algorithms: the non-frequent but damaging selection through their heuristics of particularly bad ensemble members. We introduce modified algorithms that cope with this problem by allowing individual weighting of aggregate members. Our algorithms and their weighted modifications are favorably tested against other methods in the literature, producing a sensible improvement in performance on most of the standard statistical databases used as benchmarks.
cs/0502007
Identification of complex systems in the basis of wavelets
cs.CE cs.NE
In this paper is proposed the method of the identification of complex dynamic systems. Method can be used for the identification of linear and nonlinear complex dynamic systems for the determined or stochastic signals at the inputs and the outputs. It is proposed to use a basis of wavelets for obtaining the impulse transient function (ITF) of system. ITF is considered in the form of surface in the 3D space. Are given the results of experiments on the identification of systems in the basis of wavelets.
cs/0502008
Scientific Data Management in the Coming Decade
cs.DB cs.CE
This is a thought piece on data-intensive science requirements for databases and science centers. It argues that peta-scale datasets will be housed by science centers that provide substantial storage and processing for scientists who access the data via smart notebooks. Next-generation science instruments and simulations will generate these peta-scale datasets. The need to publish and share data and the need for generic analysis and visualization tools will finally create a convergence on common metadata standards. Database systems will be judged by their support of these metadata standards and by their ability to manage and access peta-scale datasets. The procedural stream-of-bytes-file-centric approach to data analysis is both too cumbersome and too serial for such large datasets. Non-procedural query and analysis of schematized self-describing data is both easier to use and allows much more parallelism.
cs/0502009
Performance Considerations for Gigabyte per Second Transcontinental Disk-to-Disk File Transfers
cs.DB cs.PF
Moving data from CERN to Pasadena at a gigabyte per second using the next generation Internet requires good networking and good disk IO. Ten Gbps Ethernet and OC192 links are in place, so now it is simply a matter of programming. This report describes our preliminary work and measurements in configuring the disk subsystem for this effort. Using 24 SATA disks at each endpoint we are able to locally read and write an NTFS volume is striped across 24 disks at 1.2 GBps. A 32-disk stripe delivers 1.7 GBps. Experiments on higher performance and higher-capacity systems deliver up to 3.5 GBps.
cs/0502010
TerraServer SAN-Cluster Architecture and Operations Experience
cs.DC cs.DB
Microsoft TerraServer displays aerial, satellite, and to-pographic images of the earth in a SQL database available via the Internet. It is one of the most popular online at-lases, presenting seventeen terabytes of image data from the United States Geological Survey (USGS). Initially de-ployed in 1998, the system demonstrated the scalability of PC hardware and software - Windows and SQL Server - on a single, mainframe-class processor. In September 2000, the back-end database application was migrated to 4-node active/passive cluster connected to an 18 terabyte Storage Area Network (SAN). The new configuration was designed to achieve 99.99% availability for the back-end application. This paper describes the hardware and software components of the TerraServer Cluster and SAN, and describes our experience in configuring and operating this system for three years. Not surprisingly, the hardware and architecture delivered better than four-9's of availability, but operations mistakes delivered three-9's.
cs/0502011
Where the Rubber Meets the Sky: Bridging the Gap between Databases and Science
cs.DB cs.CE
Scientists in all domains face a data avalanche - both from better instruments and from improved simulations. We believe that computer science tools and computer scientists are in a position to help all the sciences by building tools and developing techniques to manage, analyze, and visualize peta-scale scientific information. This article is summarizes our experiences over the last seven years trying to bridge the gap between database technology and the needs of the astronomy community in building the World-Wide Telescope.
cs/0502015
Can Computer Algebra be Liberated from its Algebraic Yoke ?
cs.SC cs.CE
So far, the scope of computer algebra has been needlessly restricted to exact algebraic methods. Its possible extension to approximate analytical methods is discussed. The entangled roles of functional analysis and symbolic programming, especially the functional and transformational paradigms, are put forward. In the future, algebraic algorithms could constitute the core of extended symbolic manipulation systems including primitives for symbolic approximations.
cs/0502016
Stability Analysis for Regularized Least Squares Regression
cs.LG
We discuss stability for a class of learning algorithms with respect to noisy labels. The algorithms we consider are for regression, and they involve the minimization of regularized risk functionals, such as L(f) := 1/N sum_i (f(x_i)-y_i)^2+ lambda ||f||_H^2. We shall call the algorithm `stable' if, when y_i is a noisy version of f*(x_i) for some function f* in H, the output of the algorithm converges to f* as the regularization term and noise simultaneously vanish. We consider two flavors of this problem, one where a data set of N points remains fixed, and the other where N -> infinity. For the case where N -> infinity, we give conditions for convergence to f_E (the function which is the expectation of y(x) for each x), as lambda -> 0. For the fixed N case, we describe the limiting 'non-noisy', 'non-regularized' function f*, and give conditions for convergence. In the process, we develop a set of tools for dealing with functionals such as L(f), which are applicable to many other problems in learning theory.
cs/0502017
Estimating mutual information and multi--information in large networks
cs.IT cs.AI cs.CV cs.LG math.IT
We address the practical problems of estimating the information relations that characterize large networks. Building on methods developed for analysis of the neural code, we show that reliable estimates of mutual information can be obtained with manageable computational effort. The same methods allow estimation of higher order, multi--information terms. These ideas are illustrated by analyses of gene expression, financial markets, and consumer preferences. In each case, information theoretic measures correlate with independent, intuitive measures of the underlying structures in the system.
cs/0502020
Population Sizing for Genetic Programming Based Upon Decision Making
cs.AI cs.NE
This paper derives a population sizing relationship for genetic programming (GP). Following the population-sizing derivation for genetic algorithms in Goldberg, Deb, and Clark (1992), it considers building block decision making as a key facet. The analysis yields a GP-unique relationship because it has to account for bloat and for the fact that GP solutions often use subsolution multiple times. The population-sizing relationship depends upon tree size, solution complexity, problem difficulty and building block expression probability. The relationship is used to analyze and empirically investigate population sizing for three model GP problems named ORDER, ON-OFF and LOUD. These problems exhibit bloat to differing extents and differ in whether their solutions require the use of a building block multiple times.
cs/0502021
Oiling the Wheels of Change: The Role of Adaptive Automatic Problem Decomposition in Non--Stationary Environments
cs.NE cs.AI
Genetic algorithms (GAs) that solve hard problems quickly, reliably and accurately are called competent GAs. When the fitness landscape of a problem changes overtime, the problem is called non--stationary, dynamic or time--variant problem. This paper investigates the use of competent GAs for optimizing non--stationary optimization problems. More specifically, we use an information theoretic approach based on the minimum description length principle to adaptively identify regularities and substructures that can be exploited to respond quickly to changes in the environment. We also develop a special type of problems with bounded difficulties to test non--stationary optimization problems. The results provide new insights into non-stationary optimization problems and show that a search algorithm which automatically identifies and exploits possible decompositions is more robust and responds quickly to changes than a simple genetic algorithm.
cs/0502022
Sub-Structural Niching in Non-Stationary Environments
cs.NE cs.AI
Niching enables a genetic algorithm (GA) to maintain diversity in a population. It is particularly useful when the problem has multiple optima where the aim is to find all or as many as possible of these optima. When the fitness landscape of a problem changes overtime, the problem is called non--stationary, dynamic or time--variant problem. In these problems, niching can maintain useful solutions to respond quickly, reliably and accurately to a change in the environment. In this paper, we present a niching method that works on the problem substructures rather than the whole solution, therefore it has less space complexity than previously known niching mechanisms. We show that the method is responding accurately when environmental changes occur.
cs/0502023
Sub-structural Niching in Estimation of Distribution Algorithms
cs.NE cs.AI
We propose a sub-structural niching method that fully exploits the problem decomposition capability of linkage-learning methods such as the estimation of distribution algorithms and concentrate on maintaining diversity at the sub-structural level. The proposed method consists of three key components: (1) Problem decomposition and sub-structure identification, (2) sub-structure fitness estimation, and (3) sub-structural niche preservation. The sub-structural niching method is compared to restricted tournament selection (RTS)--a niching method used in hierarchical Bayesian optimization algorithm--with special emphasis on sustained preservation of multiple global solutions of a class of boundedly-difficult, additively-separable multimodal problems. The results show that sub-structural niching successfully maintains multiple global optima over large number of generations and does so with significantly less population than RTS. Additionally, the market share of each of the niche is much closer to the expected level in sub-structural niching when compared to RTS.
cs/0502024
Idempotents, Mattson-Solomon Polynomials and Binary LDPC codes
cs.IT math.IT
We show how to construct an algorithm to search for binary idempotents which may be used to construct binary LDPC codes. The algorithm, which allows control of the key properties of sparseness, code rate and minimum distance, is constructed in the Mattson-Solomon domain. Some of the new codes, found by using this technique, are displayed.
cs/0502029
Scalability of Genetic Programming and Probabilistic Incremental Program Evolution
cs.NE cs.AI
This paper discusses scalability of standard genetic programming (GP) and the probabilistic incremental program evolution (PIPE). To investigate the need for both effective mixing and linkage learning, two test problems are considered: ORDER problem, which is rather easy for any recombination-based GP, and TRAP or the deceptive trap problem, which requires the algorithm to learn interactions among subsets of terminals. The scalability results show that both GP and PIPE scale up polynomially with problem size on the simple ORDER problem, but they both scale up exponentially on the deceptive problem. This indicates that while standard recombination is sufficient when no interactions need to be considered, for some problems linkage learning is necessary. These results are in agreement with the lessons learned in the domain of binary-string genetic algorithms (GAs). Furthermore, the paper investigates the effects of introducing utnnecessary and irrelevant primitives on the performance of GP and PIPE.
cs/0502033
Pseudo-Codewords of Cycle Codes via Zeta Functions
cs.IT math.IT
Cycle codes are a special case of low-density parity-check (LDPC) codes and as such can be decoded using an iterative message-passing decoding algorithm on the associated Tanner graph. The existence of pseudo-codewords is known to cause the decoding algorithm to fail in certain instances. In this paper, we draw a connection between pseudo-codewords of cycle codes and the so-called edge zeta function of the associated normal graph and show how the Newton polyhedron of the zeta function equals the fundamental cone of the code, which plays a crucial role in characterizing the performance of iterative decoding algorithms.
cs/0502034
Multiobjective hBOA, Clustering, and Scalability
cs.NE cs.AI
This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominated sorting genetic algorithm (NSGA-II) and clustering in the objective space. It is first argued that for good scalability, clustering or some other form of niching in the objective space is necessary and the size of each niche should be approximately equal. Multiobjective hBOA (mohBOA) is then described that combines hBOA, NSGA-II and clustering in the objective space. The algorithm mohBOA differs from the multiobjective variants of BOA and hBOA proposed in the past by including clustering in the objective space and allocating an approximately equally sized portion of the population to each cluster. The algorithm mohBOA is shown to scale up well on a number of problems on which standard multiobjective evolutionary algorithms perform poorly.
cs/0502035
Near Maximum-Likelihood Performance of Some New Cyclic Codes Constructed in the Finite-Field Transform Domain
cs.IT math.IT
It is shown that some well-known and some new cyclic codes with orthogonal parity-check equations can be constructed in the finite-field transform domain. It is also shown that, for some binary linear cyclic codes, the performance of the iterative decoder can be improved by substituting some of the dual code codewords in the parity-check matrix with other dual code codewords formed from linear combinations. This technique can bring the performance of a code closer to its maximum-likelihood performance, which can be derived from the erroneous decoded codeword whose euclidean distance with the respect to the received block is smaller than that of the correct codeword. For (63,37), (93,47) and (105,53) cyclic codes, the maximum-likelihood performance is realised with this technique.
cs/0502036
Improved Iterative Decoding for Perpendicular Magnetic Recording
cs.IT math.IT
An algorithm of improving the performance of iterative decoding on perpendicular magnetic recording is presented. This algorithm follows on the authors' previous works on the parallel and serial concatenated turbo codes and low-density parity-check codes. The application of this algorithm with signal-to-noise ratio mismatch technique shows promising results in the presence of media noise. We also show that, compare to the standard iterative decoding algorithm, an improvement of within one order of magnitude can be achieved.
cs/0502037
GF(2^m) Low-Density Parity-Check Codes Derived from Cyclotomic Cosets
cs.IT math.IT
Based on the ideas of cyclotomic cosets, idempotents and Mattson-Solomon polynomials, we present a new method to construct GF(2^m), where m>0 cyclic low-density parity-check codes. The construction method produces the dual code idempotent which is used to define the parity-check matrix of the low-density parity-check code. An interesting feature of this construction method is the ability to increment the code dimension by adding more idempotents and so steadily decrease the sparseness of the parity-check matrix. We show that the constructed codes can achieve performance very close to the sphere-packing-bound constrained for binary transmission.
cs/0502042
Unified Large System Analysis of MMSE and Adaptive Least Squares Receivers for a class of Random Matrix Channels
cs.IT math.IT
We present a unified large system analysis of linear receivers for a class of random matrix channels. The technique unifies the analysis of both the minimum-mean-squared-error (MMSE) receiver and the adaptive least-squares (ALS) receiver, and also uses a common approach for both random i.i.d. and random orthogonal precoding. We derive expressions for the asymptotic signal-to-interference-plus-noise (SINR) of the MMSE receiver, and both the transient and steady-state SINR of the ALS receiver, trained using either i.i.d. data sequences or orthogonal training sequences. The results are in terms of key system parameters, and allow for arbitrary distributions of the power of each of the data streams and the eigenvalues of the channel correlation matrix. In the case of the ALS receiver, we allow a diagonal loading constant and an arbitrary data windowing function. For i.i.d. training sequences and no diagonal loading, we give a fundamental relationship between the transient/steady-state SINR of the ALS and the MMSE receivers. We demonstrate that for a particular ratio of receive to transmit dimensions and window shape, all channels which have the same MMSE SINR have an identical transient ALS SINR response. We demonstrate several applications of the results, including an optimization of information throughput with respect to training sequence length in coded block transmission.
cs/0502049
Generalised Bent Criteria for Boolean Functions (I)
cs.IT math.IT
Generalisations of the bent property of a boolean function are presented, by proposing spectral analysis with respect to a well-chosen set of local unitary transforms. Quadratic boolean functions are related to simple graphs and it is shown that the orbit generated by successive Local Complementations on a graph can be found within the transform spectra under investigation. The flat spectra of a quadratic boolean function are related to modified versions of its associated adjacency matrix.
cs/0502050
Generalised Bent Criteria for Boolean Functions (II)
cs.IT math.IT
In the first part of this paper [16], some results on how to compute the flat spectra of Boolean constructions w.r.t. the transforms {I,H}^n, {H,N}^n and {I,H,N}^n were presented, and the relevance of Local Complementation to the quadratic case was indicated. In this second part, the results are applied to develop recursive formulae for the numbers of flat spectra of some structural quadratics. Observations are made as to the generalised Bent properties of boolean functions of algebraic degree greater than two, and the number of flat spectra w.r.t. {I,H,N}^n are computed for some of them.
cs/0502052
Log Analysis Case Study Using LoGS
cs.CR cs.IR
A very useful technique a network administrator can use to identify problematic network behavior is careful analysis of logs of incoming and outgoing network flows. The challenge one faces when attempting to undertake this course of action, though, is that large networks tend to generate an extremely large quantity of network traffic in a very short period of time, resulting in very large traffic logs which must be analyzed post-generation with an eye for contextual information which may reveal symptoms of problematic traffic. A better technique is to perform real-time log analysis using a real-time context-generating tool such as LoGS.
cs/0502053
A low-cost time-hopping impulse radio system for high data rate transmission
cs.IT math.IT
We present an efficient, low-cost implementation of time-hopping impulse radio that fulfills the spectral mask mandated by the FCC and is suitable for high-data-rate, short-range communications. Key features are: (i) all-baseband implementation that obviates the need for passband components, (ii) symbol-rate (not chip rate) sampling, A/D conversion, and digital signal processing, (iii) fast acquisition due to novel search algorithms, (iv) spectral shaping that can be adapted to accommodate different spectrum regulations and interference environments. Computer simulations show that this system can provide 110Mbit/s at 7-10m distance, as well as higher data rates at shorter distances under FCC emissions limits. Due to the spreading concept of time-hopping impulse radio, the system can sustain multiple simultaneous users, and can suppress narrowband interference effectively.
cs/0502055
On quasi-cyclic interleavers for parallel turbo codes
cs.IT math.IT
We present an interleaving scheme that yields quasi-cyclic turbo codes. We prove that randomly chosen members of this family yield with probability almost 1 turbo codes with asymptotically optimum minimum distance, i.e. growing as a logarithm of the interleaver size. These interleavers are also very practical in terms of memory requirements and their decoding error probabilities for small block lengths compare favorably with previous interleaving schemes.
cs/0502057
Decomposable Problems, Niching, and Scalability of Multiobjective Estimation of Distribution Algorithms
cs.NE cs.AI
The paper analyzes the scalability of multiobjective estimation of distribution algorithms (MOEDAs) on a class of boundedly-difficult additively-separable multiobjective optimization problems. The paper illustrates that even if the linkage is correctly identified, massive multimodality of the search problems can easily overwhelm the nicher and lead to exponential scale-up. Facetwise models are subsequently used to propose a growth rate of the number of differing substructures between the two objectives to avoid the niching method from being overwhelmed and lead to polynomial scalability of MOEDAs.
cs/0502060
Perspectives for Strong Artificial Life
cs.AI
This text introduces the twin deadlocks of strong artificial life. Conceptualization of life is a deadlock both because of the existence of a continuum between the inert and the living, and because we only know one instance of life. Computationalism is a second deadlock since it remains a matter of faith. Nevertheless, artificial life realizations quickly progress and recent constructions embed an always growing set of the intuitive properties of life. This growing gap between theory and realizations should sooner or later crystallize in some kind of paradigm shift and then give clues to break the twin deadlocks.
cs/0502063
Nonlinear MMSE Multiuser Detection Based on Multivariate Gaussian Approximation
cs.IT math.IT
In this paper, a class of nonlinear MMSE multiuser detectors are derived based on a multivariate Gaussian approximation of the multiple access interference. This approach leads to expressions identical to those describing the probabilistic data association (PDA) detector, thus providing an alternative analytical justification for this structure. A simplification to the PDA detector based on approximating the covariance matrix of the multivariate Gaussian distribution is suggested, resulting in a soft interference cancellation scheme. Corresponding multiuser soft-input, soft-output detectors delivering extrinsic log-likelihood ratios are derived for application in iterative multiuser decoders. Finally, a large system performance analysis is conducted for the simplified PDA, showing that the bit error rate performance of this detector can be accurately predicted and related to the replica method analysis for the optimal detector. Methods from statistical neuro-dynamics are shown to provide a closely related alternative large system prediction. Numerical results demonstrate that for large systems, the bit error rate is accurately predicted by the analysis and found to be close to optimal performance.
cs/0502067
Master Algorithms for Active Experts Problems based on Increasing Loss Values
cs.LG cs.AI
We specify an experts algorithm with the following characteristics: (a) it uses only feedback from the actions actually chosen (bandit setup), (b) it can be applied with countably infinite expert classes, and (c) it copes with losses that may grow in time appropriately slowly. We prove loss bounds against an adaptive adversary. From this, we obtain master algorithms for "active experts problems", which means that the master's actions may influence the behavior of the adversary. Our algorithm can significantly outperform standard experts algorithms on such problems. Finally, we combine it with a universal expert class. This results in a (computationally infeasible) universal master algorithm which performs - in a certain sense - almost as well as any computable strategy, for any online problem.
cs/0502071
Analysis of Second-order Statistics Based Semi-blind Channel Estimation in CDMA Channels
cs.IT math.IT
The performance of second order statistics (SOS) based semi-blind channel estimation in long-code DS-CDMA systems is analyzed. The covariance matrix of SOS estimates is obtained in the large system limit, and is used to analyze the large-sample performance of two SOS based semi-blind channel estimation algorithms. A notion of blind estimation efficiency is also defined and is examined via simulation results.
cs/0502072
Batch is back: CasJobs, serving multi-TB data on the Web
cs.DC cs.DB
The Sloan Digital Sky Survey (SDSS) science database describes over 140 million objects and is over 1.5 TB in size. The SDSS Catalog Archive Server (CAS) provides several levels of query interface to the SDSS data via the SkyServer website. Most queries execute in seconds or minutes. However, some queries can take hours or days, either because they require non-index scans of the largest tables, or because they request very large result sets, or because they represent very complex aggregations of the data. These "monster queries" not only take a long time, they also affect response times for everyone else - one or more of them can clog the entire system. To ameliorate this problem, we developed a multi-server multi-queue batch job submission and tracking system for the CAS called CasJobs. The transfer of very large result sets from queries over the network is another serious problem. Statistics suggested that much of this data transfer is unnecessary; users would prefer to store results locally in order to allow further joins and filtering. To allow local analysis, a system was developed that gives users their own personal databases (MyDB) at the server side. Users may transfer data to their MyDB, and then perform further analysis before extracting it to their own machine. MyDB tables also provide a convenient way to share results of queries with collaborators without downloading them. CasJobs is built using SOAP XML Web services and has been in operation since May 2004.
cs/0502074
On sample complexity for computational pattern recognition
cs.LG cs.CC
In statistical setting of the pattern recognition problem the number of examples required to approximate an unknown labelling function is linear in the VC dimension of the target learning class. In this work we consider the question whether such bounds exist if we restrict our attention to computable pattern recognition methods, assuming that the unknown labelling function is also computable. We find that in this case the number of examples required for a computable method to approximate the labelling function not only is not linear, but grows faster (in the VC dimension of the class) than any computable function. No time or space constraints are put on the predictors or target functions; the only resource we consider is the training examples. The task of pattern recognition is considered in conjunction with another learning problem -- data compression. An impossibility result for the task of data compression allows us to estimate the sample complexity for pattern recognition.
cs/0502075
How far will you walk to find your shortcut: Space Efficient Synopsis Construction Algorithms
cs.DS cs.DB
In this paper we consider the wavelet synopsis construction problem without the restriction that we only choose a subset of coefficients of the original data. We provide the first near optimal algorithm. We arrive at the above algorithm by considering space efficient algorithms for the restricted version of the problem. In this context we improve previous algorithms by almost a linear factor and reduce the required space to almost linear. Our techniques also extend to histogram construction, and improve the space-running time tradeoffs for V-Opt and range query histograms. We believe the idea applies to a broad range of dynamic programs and demonstrate it by showing improvements in a knapsack-like setting seen in construction of Extended Wavelets.
cs/0502076
Learning nonsingular phylogenies and hidden Markov models
cs.LG cs.CE math.PR math.ST q-bio.PE stat.TH
In this paper we study the problem of learning phylogenies and hidden Markov models. We call a Markov model nonsingular if all transition matrices have determinants bounded away from 0 (and 1). We highlight the role of the nonsingularity condition for the learning problem. Learning hidden Markov models without the nonsingularity condition is at least as hard as learning parity with noise, a well-known learning problem conjectured to be computationally hard. On the other hand, we give a polynomial-time algorithm for learning nonsingular phylogenies and hidden Markov models.
cs/0502077
On the Achievable Information Rates of Finite-State Input Two-Dimensional Channels with Memory
cs.IT math.IT
The achievable information rate of finite-state input two-dimensional (2-D) channels with memory is an open problem, which is relevant, e.g., for inter-symbol-interference (ISI) channels and cellular multiple-access channels. We propose a method for simulation-based computation of such information rates. We first draw a connection between the Shannon-theoretic information rate and the statistical mechanics notion of free energy. Since the free energy of such systems is intractable, we approximate it using the cluster variation method, implemented via generalized belief propagation. The derived, fully tractable, algorithm is shown to provide a practically accurate estimate of the information rate. In our experimental study we calculate the information rates of 2-D ISI channels and of hexagonal Wyner cellular networks with binary inputs, for which formerly only bounds were known.
cs/0502078
Semantical Characterizations and Complexity of Equivalences in Answer Set Programming
cs.AI cs.CC
In recent research on non-monotonic logic programming, repeatedly strong equivalence of logic programs P and Q has been considered, which holds if the programs P union R and Q union R have the same answer sets for any other program R. This property strengthens equivalence of P and Q with respect to answer sets (which is the particular case for R is the empty set), and has its applications in program optimization, verification, and modular logic programming. In this paper, we consider more liberal notions of strong equivalence, in which the actual form of R may be syntactically restricted. On the one hand, we consider uniform equivalence, where R is a set of facts rather than a set of rules. This notion, which is well known in the area of deductive databases, is particularly useful for assessing whether programs P and Q are equivalent as components of a logic program which is modularly structured. On the other hand, we consider relativized notions of equivalence, where R ranges over rules over a fixed alphabet, and thus generalize our results to relativized notions of strong and uniform equivalence. For all these notions, we consider disjunctive logic programs in the propositional (ground) case, as well as some restricted classes, provide semantical characterizations and analyze the computational complexity. Our results, which naturally extend to answer set semantics for programs with strong negation, complement the results on strong equivalence of logic programs and pave the way for optimizations in answer set solvers as a tool for input-based problem solving.
cs/0502079
Multilevel expander codes
cs.IT math.IT
We define multilevel codes on bipartite graphs that have properties analogous to multilevel serial concatenations. A decoding algorithm is described that corrects a proportion of errors equal to half the Blokh-Zyablov bound on the minimum distance. The error probability of this algorithm has exponent similar to that of serially concatenated multilevel codes.
cs/0502080
Sensor Configuration and Activation for Field Detection in Large Sensor Arrays
cs.IT math.IT
The problems of sensor configuration and activation for the detection of correlated random fields using large sensor arrays are considered. Using results that characterize the large-array performance of sensor networks in this application, the detection capabilities of different sensor configurations are analyzed and compared. The dependence of the optimal choice of configuration on parameters such as sensor signal-to-noise ratio (SNR), field correlation, etc., is examined, yielding insights into the most effective choices for sensor selection and activation in various operating regimes.
cs/0502081
Tables, Memorized Semirings and Applications
cs.MA cs.DM
We define and construct a new data structure, the tables, this structure generalizes the (finite) $k$-sets sets of Eilenberg \cite{Ei}, it is versatile (one can vary the letters, the words and the coefficients). We derive from this structure a new semiring (with several semiring structures) which can be applied to the needs of automatic processing multi-agents behaviour problems. The purpose of this account/paper is to present also the basic elements of this new structures from a combinatorial point of view. These structures present a bunch of properties. They will be endowed with several laws namely : Sum, Hadamard product, Cauchy product, Fuzzy operations (min, max, complemented product) Two groups of applications are presented. The first group is linked to the process of "forgetting" information in the tables. The second, linked to multi-agent systems, is announced by showing a methodology to manage emergent organization from individual behaviour models.
cs/0502082
Graphs and colorings for answer set programming
cs.AI cs.LO
We investigate the usage of rule dependency graphs and their colorings for characterizing and computing answer sets of logic programs. This approach provides us with insights into the interplay between rules when inducing answer sets. We start with different characterizations of answer sets in terms of totally colored dependency graphs that differ in graph-theoretical aspects. We then develop a series of operational characterizations of answer sets in terms of operators on partial colorings. In analogy to the notion of a derivation in proof theory, our operational characterizations are expressed as (non-deterministically formed) sequences of colorings, turning an uncolored graph into a totally colored one. In this way, we obtain an operational framework in which different combinations of operators result in different formal properties. Among others, we identify the basic strategy employed by the noMoRe system and justify its algorithmic approach. Furthermore, we distinguish operations corresponding to Fitting's operator as well as to well-founded semantics. (To appear in Theory and Practice of Logic Programming (TPLP))
cs/0502083
Impulse Radio Systems with Multiple Types of Ultra-Wideband Pulses
cs.IT math.IT
Spectral properties and performance of multi-pulse impulse radio ultra-wideband systems with pulse-based polarity randomization are analyzed. Instead of a single type of pulse transmitted in each frame, multiple types of pulses are considered, which is shown to reduce the effects of multiple-access interference. First, the spectral properties of a multi-pulse impulse radio system is investigated. It is shown that the power spectral density is the average of spectral contents of different pulse shapes. Then, approximate closed-form expressions for bit error probability of a multi-pulse impulse radio system are derived for RAKE receivers in asynchronous multiuser environments. The theoretical and simulation results indicate that impulse radio systems that are more robust against multiple-access interference than a "classical" impulse radio system can be designed with multiple types of ultra-wideband pulses.
cs/0502084
On the Typicality of the Linear Code Among the LDPC Coset Code Ensemble
cs.IT math.IT
Density evolution (DE) is one of the most powerful analytical tools for low-density parity-check (LDPC) codes on memoryless binary-input/symmetric-output channels. The case of non-symmetric channels is tackled either by the LDPC coset code ensemble (a channel symmetrizing argument) or by the generalized DE for linear codes on non-symmetric channels. Existing simulations show that the bit error rate performances of these two different approaches are nearly identical. This paper explains this phenomenon by proving that as the minimum check node degree $d_c$ becomes sufficiently large, the performance discrepancy of the linear and the coset LDPC codes is theoretically indistinguishable. This typicality of linear codes among the LDPC coset code ensemble provides insight into the concentration theorem of LDPC coset codes.
cs/0502086
The Self-Organization of Speech Sounds
cs.LG cs.AI cs.CL cs.NE cs.RO math.DS
The speech code is a vehicle of language: it defines a set of forms used by a community to carry information. Such a code is necessary to support the linguistic interactions that allow humans to communicate. How then may a speech code be formed prior to the existence of linguistic interactions? Moreover, the human speech code is discrete and compositional, shared by all the individuals of a community but different across communities, and phoneme inventories are characterized by statistical regularities. How can a speech code with these properties form? We try to approach these questions in the paper, using the "methodology of the artificial". We build a society of artificial agents, and detail a mechanism that shows the formation of a discrete speech code without pre-supposing the existence of linguistic capacities or of coordinated interactions. The mechanism is based on a low-level model of sensory-motor interactions. We show that the integration of certain very simple and non language-specific neural devices leads to the formation of a speech code that has properties similar to the human speech code. This result relies on the self-organizing properties of a generic coupling between perception and production within agents, and on the interactions between agents. The artificial system helps us to develop better intuitions on how speech might have appeared, by showing how self-organization might have helped natural selection to find speech.
cs/0502087
Self-Replicating Strands that Self-Assemble into User-Specified Meshes
cs.NE cs.CE cs.MA
It has been argued that a central objective of nanotechnology is to make products inexpensively, and that self-replication is an effective approach to very low-cost manufacturing. The research presented here is intended to be a step towards this vision. In previous work (JohnnyVon 1.0), we simulated machines that bonded together to form self-replicating strands. There were two types of machines (called types 0 and 1), which enabled strands to encode arbitrary bit strings. However, the information encoded in the strands had no functional role in the simulation. The information was replicated without being interpreted, which was a significant limitation for potential manufacturing applications. In the current work (JohnnyVon 2.0), the information in a strand is interpreted as instructions for assembling a polygonal mesh. There are now four types of machines and the information encoded in a strand determines how it folds. A strand may be in an unfolded state, in which the bonds are straight (although they flex slightly due to virtual forces acting on the machines), or in a folded state, in which the bond angles depend on the types of machines. By choosing the sequence of machine types in a strand, the user can specify a variety of polygonal shapes. A simulation typically begins with an initial unfolded seed strand in a soup of unbonded machines. The seed strand replicates by bonding with free machines in the soup. The child strands fold into the encoded polygonal shape, and then the polygons drift together and bond to form a mesh. We demonstrate that a variety of polygonal meshes can be manufactured in the simulation, by simply changing the sequence of machine types in the seed.
cs/0502088
Towards a Systematic Account of Different Semantics for Logic Programs
cs.AI cs.LO
In [Hitzler and Wendt 2002, 2005], a new methodology has been proposed which allows to derive uniform characterizations of different declarative semantics for logic programs with negation. One result from this work is that the well-founded semantics can formally be understood as a stratified version of the Fitting (or Kripke-Kleene) semantics. The constructions leading to this result, however, show a certain asymmetry which is not readily understood. We will study this situation here with the result that we will obtain a coherent picture of relations between different semantics for normal logic programs.
cs/0502094
Coalition Formation: Concessions, Task Relationships and Complexity Reduction
cs.MA
Solutions to the coalition formation problem commonly assume agent rationality and, correspondingly, utility maximization. This in turn may prevent agents from making compromises. As shown in recent studies, compromise may facilitate coalition formation and increase agent utilities. In this study we leverage on those new results. We devise a novel coalition formation mechanism that enhances compromise. Our mechanism can utilize information on task dependencies to reduce formation complexity. Further, it works well with both cardinal and ordinal task values. Via experiments we show that the use of the suggested compromise-based coalition formation mechanism provides significant savings in the computation and communication complexity of coalition formation. Our results also show that when information on task dependencies is used, the complexity of coalition formation is further reduced. We demonstrate successful use of the mechanism for collaborative information filtering, where agents combine linguistic rules to analyze documents' contents.
cs/0502095
Gradient Vector Flow Models for Boundary Extraction in 2D Images
cs.CV
The Gradient Vector Flow (GVF) is a vector diffusion approach based on Partial Differential Equations (PDEs). This method has been applied together with snake models for boundary extraction medical images segmentation. The key idea is to use a diffusion-reaction PDE to generate a new external force field that makes snake models less sensitivity to initialization as well as improves the snake's ability to move into boundary concavities. In this paper, we firstly review basic results about convergence and numerical analysis of usual GVF schemes. We point out that GVF presents numerical problems due to discontinuities image intensity. This point is considered from a practical viewpoint from which the GVF parameters must follow a relationship in order to improve numerical convergence. Besides, we present an analytical analysis of the GVF dependency from the parameters values. Also, we observe that the method can be used for multiply connected domains by just imposing the suitable boundary condition. In the experimental results we verify these theoretical points and demonstrate the utility of GVF on a segmentation approach that we have developed based on snakes.
cs/0502096
Property analysis of symmetric travelling salesman problem instances acquired through evolution
cs.NE cs.AI
We show how an evolutionary algorithm can successfully be used to evolve a set of difficult to solve symmetric travelling salesman problem instances for two variants of the Lin-Kernighan algorithm. Then we analyse the instances in those sets to guide us towards deferring general knowledge about the efficiency of the two variants in relation to structural properties of the symmetric travelling sale sman problem.
cs/0503001
Top-Down Unsupervised Image Segmentation (it sounds like oxymoron, but actually it is not)
cs.CV cs.IR
Pattern recognition is generally assumed as an interaction of two inversely directed image-processing streams: the bottom-up information details gathering and localization (segmentation) stream, and the top-down information features aggregation, association and interpretation (recognition) stream. Inspired by recent evidence from biological vision research and by the insights of Kolmogorov Complexity theory, we propose a new, just top-down evolving, procedure of initial image segmentation. We claim that traditional top-down cognitive reasoning, which is supposed to guide the segmentation process to its final result, is not at all a part of the image information content evaluation. And that initial image segmentation is certainly an unsupervised process. We present some illustrative examples, which support our claims.
cs/0503006
A New Non-Iterative Decoding Algorithm for the Erasure Channel : Comparisons with Enhanced Iterative Methods
cs.IT math.IT
This paper investigates decoding of binary linear block codes over the binary erasure channel (BEC). Of the current iterative decoding algorithms on this channel, we review the Recovery Algorithm and the Guess Algorithm. We then present a Multi-Guess Algorithm extended from the Guess Algorithm and a new algorithm -- the In-place Algorithm. The Multi-Guess Algorithm can push the limit to break the stopping sets. However, the performance of the Guess and the Multi-Guess Algorithm depend on the parity-check matrix of the code. Simulations show that we can decrease the frame error rate by several orders of magnitude using the Guess and the Multi-Guess Algorithms when the parity-check matrix of the code is sparse. The In-place Algorithm can obtain better performance even if the parity check matrix is dense. We consider the application of these algorithms in the implementation of multicast and broadcast techniques on the Internet. Using these algorithms, a user does not have to wait until the entire transmission has been received.
cs/0503011
Shuffling a Stacked Deck: The Case for Partially Randomized Ranking of Search Engine Results
cs.IR
In-degree, PageRank, number of visits and other measures of Web page popularity significantly influence the ranking of search results by modern search engines. The assumption is that popularity is closely correlated with quality, a more elusive concept that is difficult to measure directly. Unfortunately, the correlation between popularity and quality is very weak for newly-created pages that have yet to receive many visits and/or in-links. Worse, since discovery of new content is largely done by querying search engines, and because users usually focus their attention on the top few results, newly-created but high-quality pages are effectively ``shut out,'' and it can take a very long time before they become popular. We propose a simple and elegant solution to this problem: the introduction of a controlled amount of randomness into search result ranking methods. Doing so offers new pages a chance to prove their worth, although clearly using too much randomness will degrade result quality and annul any benefits achieved. Hence there is a tradeoff between exploration to estimate the quality of new pages and exploitation of pages already known to be of high quality. We study this tradeoff both analytically and via simulation, in the context of an economic objective function based on aggregate result quality amortized over time. We show that a modest amount of randomness leads to improved search results.
cs/0503012
First-order Complete and Computationally Complete Query Languages for Spatio-Temporal Databases
cs.DB
We address a fundamental question concerning spatio-temporal database systems: ``What are exactly spatio-temporal queries?'' We define spatio-temporal queries to be computable mappings that are also generic, meaning that the result of a query may only depend to a limited extent on the actual internal representation of the spatio-temporal data. Genericity is defined as invariance under groups of geometric transformations that preserve certain characteristics of spatio-temporal data (e.g., collinearity, distance, velocity, acceleration, ...). These groups depend on the notions that are relevant in particular spatio-temporal database applications. These transformations also have the distinctive property that they respect the monotone and unidirectional nature of time. We investigate different genericity classes with respect to the constraint database model for spatio-temporal databases and we identify sound and complete languages for the first-order and the computable queries in these genericity classes. We distinguish between genericity determined by time-invariant transformations, genericity notions concerning physical quantities and genericity determined by time-dependent transformations.
cs/0503018
Probabilistic Algorithmic Knowledge
cs.AI cs.LO
The framework of algorithmic knowledge assumes that agents use deterministic knowledge algorithms to compute the facts they explicitly know. We extend the framework to allow for randomized knowledge algorithms. We then characterize the information provided by a randomized knowledge algorithm when its answers have some probability of being incorrect. We formalize this information in terms of evidence; a randomized knowledge algorithm returning ``Yes'' to a query about a fact \phi provides evidence for \phi being true. Finally, we discuss the extent to which this evidence can be used as a basis for decisions.
cs/0503019
Duality Bounds on the Cut-Off Rate with Applications to Ricean Fading
cs.IT math.IT
We propose a technique to derive upper bounds on Gallager's cost-constrained random coding exponent function. Applying this technique to the non-coherent peak-power or average-power limited discrete time memoryless Ricean fading channel, we obtain the high signal-to-noise ratio (SNR) expansion of this channel's cut-off rate. At high SNR the gap between channel capacity and the cut-off rate approaches a finite limit. This limit is approximately 0.26 nats per channel-use for zero specular component (Rayleigh) fading and approaches 0.39 nats per channel-use for very large specular components. We also compute the asymptotic cut-off rate of a Rayleigh fading channel when the receiver has access to some partial side information concerning the fading. It is demonstrated that the cut-off rate does not utilize the side information as efficiently as capacity, and that the high SNR gap between the two increases to infinity as the imperfect side information becomes more and more precise.
cs/0503020
Earlier Web Usage Statistics as Predictors of Later Citation Impact
cs.IR
The use of citation counts to assess the impact of research articles is well established. However, the citation impact of an article can only be measured several years after it has been published. As research articles are increasingly accessed through the Web, the number of times an article is downloaded can be instantly recorded and counted. One would expect the number of times an article is read to be related both to the number of times it is cited and to how old the article is. This paper analyses how short-term Web usage impact predicts medium-term citation impact. The physics e-print archive (arXiv.org) is used to test this.
cs/0503021
Fast-Forward on the Green Road to Open Access: The Case Against Mixing Up Green and Gold
cs.IR
This article is a critique of: "The 'Green' and 'Gold' Roads to Open Access: The Case for Mixing and Matching" by Jean-Claude Guedon (in Serials Review 30(4) 2004). Open Access (OA) means: free online access to all peer-reviewed journal articles. Jean-Claude Guedon argues against the efficacy of author self-archiving of peer-reviewed journal articles (the "Green" road to OA). He suggests instead that we should convert to Open Access Publishing (the "Golden" road to OA) by "mixing and matching" Green and Gold as follows: o First, self-archive dissertations (not published, peer-reviewed journal articles). o Second, identify and tag how those dissertations have been evaluated and reviewed. o Third, self-archive unrefereed preprints (not published, peer-reviewed journal articles). o Fourth, develop new mechanisms for evaluating and reviewing those unrefereed preprints, at multiple levels. The result will be OA Publishing (Gold). I argue that rather than yet another 10 years of speculation like this, what is actually needed (and imminent) is for OA self-archiving to be mandated by research funders and institutions so that the self-archiving of published, peer-reviewed journal articles (Green) can be fast-forwarded to 100% OA.
cs/0503022
Theory and Practice of Transactional Method Caching
cs.DB
Nowadays, tiered architectures are widely accepted for constructing large scale information systems. In this context application servers often form the bottleneck for a system's efficiency. An application server exposes an object oriented interface consisting of set of methods which are accessed by potentially remote clients. The idea of method caching is to store results of read-only method invocations with respect to the application server's interface on the client side. If the client invokes the same method with the same arguments again, the corresponding result can be taken from the cache without contacting the server. It has been shown that this approach can considerably improve a real world system's efficiency. This paper extends the concept of method caching by addressing the case where clients wrap related method invocations in ACID transactions. Demarcating sequences of method calls in this way is supported by many important application server standards. In this context the paper presents an architecture, a theory and an efficient protocol for maintaining full transactional consistency and in particular serializability when using a method cache on the client side. In order to create a protocol for scheduling cached method results, the paper extends a classical transaction formalism. Based on this extension, a recovery protocol and an optimistic serializability protocol are derived. The latter one differs from traditional transactional cache protocols in many essential ways. An efficiency experiment validates the approach: Using the cache a system's performance and scalability are considerably improved.
cs/0503024
Fine-Grained Word Sense Disambiguation Based on Parallel Corpora, Word Alignment, Word Clustering and Aligned Wordnets
cs.AI cs.CL
The paper presents a method for word sense disambiguation based on parallel corpora. The method exploits recent advances in word alignment and word clustering based on automatic extraction of translation equivalents and being supported by available aligned wordnets for the languages in the corpus. The wordnets are aligned to the Princeton Wordnet, according to the principles established by EuroWordNet. The evaluation of the WSD system, implementing the method described herein showed very encouraging results. The same system used in a validation mode, can be used to check and spot alignment errors in multilingually aligned wordnets as BalkaNet and EuroWordNet.
cs/0503026
On Generalized Computable Universal Priors and their Convergence
cs.LG cs.CC math.PR
Solomonoff unified Occam's razor and Epicurus' principle of multiple explanations to one elegant, formal, universal theory of inductive inference, which initiated the field of algorithmic information theory. His central result is that the posterior of the universal semimeasure M converges rapidly to the true sequence generating posterior mu, if the latter is computable. Hence, M is eligible as a universal predictor in case of unknown mu. The first part of the paper investigates the existence and convergence of computable universal (semi)measures for a hierarchy of computability classes: recursive, estimable, enumerable, and approximable. For instance, M is known to be enumerable, but not estimable, and to dominate all enumerable semimeasures. We present proofs for discrete and continuous semimeasures. The second part investigates more closely the types of convergence, possibly implied by universality: in difference and in ratio, with probability 1, in mean sum, and for Martin-Loef random sequences. We introduce a generalized concept of randomness for individual sequences and use it to exhibit difficulties regarding these issues. In particular, we show that convergence fails (holds) on generalized-random sequences in gappy (dense) Bernoulli classes.
cs/0503027
Authentication with Distortion Criteria
cs.IT cs.CR cs.MM math.IT
In a variety of applications, there is a need to authenticate content that has experienced legitimate editing in addition to potential tampering attacks. We develop one formulation of this problem based on a strict notion of security, and characterize and interpret the associated information-theoretic performance limits. The results can be viewed as a natural generalization of classical approaches to traditional authentication. Additional insights into the structure of such systems and their behavior are obtained by further specializing the results to Bernoulli and Gaussian cases. The associated systems are shown to be substantially better in terms of performance and/or security than commonly advocated approaches based on data hiding and digital watermarking. Finally, the formulation is extended to obtain efficient layered authentication system constructions.
cs/0503028
Stabilization of Cooperative Information Agents in Unpredictable Environment: A Logic Programming Approach
cs.LO cs.MA cs.PL
An information agent is viewed as a deductive database consisting of 3 parts: an observation database containing the facts the agent has observed or sensed from its surrounding environment, an input database containing the information the agent has obtained from other agents, and an intensional database which is a set of rules for computing derived information from the information stored in the observation and input databases. Stabilization of a system of information agents represents a capability of the agents to eventually get correct information about their surrounding despite unpredictable environment changes and the incapability of many agents to sense such changes causing them to have temporary incorrect information. We argue that the stabilization of a system of cooperative information agents could be understood as the convergence of the behavior of the whole system toward the behavior of a "superagent", who has the sensing and computing capabilities of all agents combined. We show that unfortunately, stabilization is not guaranteed in general, even if the agents are fully cooperative and do not hide any information from each other. We give sufficient conditions for stabilization and discuss the consequences of our results.
cs/0503030
A Suffix Tree Approach to Email Filtering
cs.AI cs.CL
We present an approach to email filtering based on the suffix tree data structure. A method for the scoring of emails using the suffix tree is developed and a number of scoring and score normalisation functions are tested. Our results show that the character level representation of emails and classes facilitated by the suffix tree can significantly improve classification accuracy when compared with the currently popular methods, such as naive Bayes. We believe the method can be extended to the classification of documents in other domains.
cs/0503031
On the Scalability of Cooperative Time Synchronization in Pulse-Connected Networks
cs.IT math.IT nlin.AO
The problem of time synchronization in dense wireless networks is considered. Well established synchronization techniques suffer from an inherent scalability problem in that synchronization errors grow with an increasing number of hops across the network. In this work, a model for communication in wireless networks is first developed, and then the model is used to define a new time synchronization mechanism. A salient feature of the proposed method is that, in the regime of asymptotically dense networks, it can average out all random errors and maintain global synchronization in the sense that all nodes in the multi-hop network can see identical timing signals. This is irrespective of the distance separating any two nodes.
cs/0503032
Complexity and Approximation of Fixing Numerical Attributes in Databases Under Integrity Constraints
cs.DB cs.CC
Consistent query answering is the problem of computing the answers from a database that are consistent with respect to certain integrity constraints that the database as a whole may fail to satisfy. Those answers are characterized as those that are invariant under minimal forms of restoring the consistency of the database. In this context, we study the problem of repairing databases by fixing integer numerical values at the attribute level with respect to denial and aggregation constraints. We introduce a quantitative definition of database fix, and investigate the complexity of several decision and optimization problems, including DFP, i.e. the existence of fixes within a given distance from the original instance, and CQA, i.e. deciding consistency of answers to aggregate conjunctive queries under different semantics. We provide sharp complexity bounds, identify relevant tractable cases; and introduce approximation algorithms for some of those that are intractable. More specifically, we obtain results like undecidability of existence of fixes for aggregation constraints; MAXSNP-hardness of DFP, but a good approximation algorithm for a relevant special case; and intractability but good approximation for CQA for aggregate queries for one database atom denials (plus built-ins).