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Title: Fictitious Play with Time-Invariant Frequency Update for Network Security |
Abstract: We study two-player security games which can be viewed as sequences of nonzero-sum matrix games played by an Attacker and a Defender. The evolution of the game is based on a stochastic fictitious play process, where players do not have access to each other's payoff matrix. Each has to observe the other's acti... |
Title: On signal and extraneous roots in Singular Spectrum Analysis |
Abstract: In the present paper we study properties of roots of characteristic polynomials for the linear recurrent formulae (LRF) that govern time series. We also investigate how the values of these roots affect Singular Spectrum Analysis implications, in what concerns separation of components, SSA forecasting and rela... |
Title: Algorithm for Sector Spectra Calculation from Images Registered by the Spectral Airglow Temperature Imager |
Abstract: The Spectral Airglow Temperature Imager is an instrument, specially designed for investigation of the wave processes in the Mesosphere-Lower Thermosphere. In order to determine the kinematic parameters of a wave, the values of a physical quantity in different space points and their changes in the time should ... |
Title: Action Recognition in Videos: from Motion Capture Labs to the Web |
Abstract: This paper presents a survey of human action recognition approaches based on visual data recorded from a single video camera. We propose an organizing framework which puts in evidence the evolution of the area, with techniques moving from heavily constrained motion capture scenarios towards more challenging, ... |
Title: Gaussian Mixture Modeling with Gaussian Process Latent Variable Models |
Abstract: Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristics of the data. Recently, the Gaussian Process Latent Variable Model (GPLVM) has successfully been used to find low dimensional ma... |
Title: The Use of Probabilistic Systems to Mimic the Behaviour of Idiotypic AIS Robot Controllers |
Abstract: Previous work has shown that robot navigation systems that employ an architecture based upon the idiotypic network theory of the immune system have an advantage over control techniques that rely on reinforcement learning only. This is thought to be a result of intelligent behaviour selection on the part of th... |
Title: Modelling Reactive and Proactive Behaviour in Simulation |
Abstract: This research investigated the simulation model behaviour of a traditional and combined discrete event as well as agent based simulation models when modelling human reactive and proactive behaviour in human centric complex systems. A departmental store was chosen as human centric complex case study where the ... |
Title: Detecting Anomalous Process Behaviour using Second Generation Artificial Immune Systems |
Abstract: Artificial Immune Systems have been successfully applied to a number of problem domains including fault tolerance and data mining, but have been shown to scale poorly when applied to computer intrusion detec- tion despite the fact that the biological immune system is a very effective anomaly detector. This ma... |
Title: Functional Answer Set Programming |
Abstract: In this paper we propose an extension of Answer Set Programming (ASP), and in particular, of its most general logical counterpart, Quantified Equilibrium Logic (QEL), to deal with partial functions. Although the treatment of equality in QEL can be established in different ways, we first analyse the choice of ... |
Title: Segmentation of Natural Images by Texture and Boundary Compression |
Abstract: We present a novel algorithm for segmentation of natural images that harnesses the principle of minimum description length (MDL). Our method is based on observations that a homogeneously textured region of a natural image can be well modeled by a Gaussian distribution and the region boundary can be effectivel... |
Title: Adaptive Optimal Scaling of Metropolis-Hastings Algorithms Using the Robbins-Monro Process |
Abstract: We present an adaptive method for the automatic scaling of Random-Walk Metropolis-Hastings algorithms, which quickly and robustly identifies the scaling factor that yields a specified overall sampler acceptance probability. Our method relies on the use of the Robbins-Monro search process, whose performance is... |
Title: Redescending M-estimators and Deterministic Annealing, with Applications to Robust Regression and Tail Index Estimation |
Abstract: A new type of redescending M-estimators is constructed, based on data augmentation with an unspecified outlier model. Necessary and sufficient conditions for the convergence of the resulting estimators to the Hubertype skipped mean are derived. By introducing a temperature parameter the concept of determinist... |
Title: G1-Renewal Process as Repairable System Model |
Abstract: This paper considers a point process model with a monotonically decreasing or increasing ROCOF and the underlying distributions from the location-scale family, known as the geometric process (Lam, 1988). In terms of repairable system reliability analysis, the process is capable of modeling various restoration... |
Title: Using Integrated Nested Laplace Approximation for Modeling Spatial Healthcare Utilization |
Abstract: In recent years, spatial and spatio-temporal modeling have become an important area of research in many fields (epidemiology, environmental studies, disease mapping). In this work we propose different spatial models to study hospital recruitment, including some potentially explicative variables. Interest is o... |
Title: Least Squares Superposition Codes of Moderate Dictionary Size, Reliable at Rates up to Capacity |
Abstract: For the additive white Gaussian noise channel with average codeword power constraint, new coding methods are devised in which the codewords are sparse superpositions, that is, linear combinations of subsets of vectors from a given design, with the possible messages indexed by the choice of subset. Decoding is... |
Title: Complete Complementary Results Report of the MARF's NLP Approach to the DEFT 2010 Competition |
Abstract: This companion paper complements the main DEFT'10 article describing the MARF approach (arXiv:0905.1235) to the DEFT'10 NLP challenge (described at http://www.groupes.polymtl.ca/taln2010/deft.php in French). This paper is aimed to present the complete result sets of all the conducted experiments and their set... |
Title: About incoherent inference |
Abstract: In Templeton (2010), the Approximate Bayesian Computation (ABC) algorithm (see, e.g., Pritchard et al., 1999, Beaumont et al., 2002, Marjoram et al., 2003, Ratmann et al., 2009) is criticised on mathematical and logical grounds: "the [Bayesian] inference is mathematically incorrect and formally illogical". Si... |
Title: Toward Fast Reliable Communication at Rates Near Capacity with Gaussian Noise |
Abstract: For the additive Gaussian noise channel with average codeword power constraint, sparse superposition codes and adaptive successive decoding is developed. Codewords are linear combinations of subsets of vectors, with the message indexed by the choice of subset. A feasible decoding algorithm is presented. Commu... |
Title: Heavy-Tailed Processes for Selective Shrinkage |
Abstract: Heavy-tailed distributions are frequently used to enhance the robustness of regression and classification methods to outliers in output space. Often, however, we are confronted with "outliers" in input space, which are isolated observations in sparsely populated regions. We show that heavy-tailed stochastic p... |
Title: Graph-Valued Regression |
Abstract: Undirected graphical models encode in a graph $G$ the dependency structure of a random vector $Y$. In many applications, it is of interest to model $Y$ given another random vector $X$ as input. We refer to the problem of estimating the graph $G(x)$ of $Y$ conditioned on $X=x$ as ``graph-valued regression.'' I... |
Title: Towards the Development of a Simulator for Investigating the Impact of People Management Practices on Retail Performance |
Abstract: Often models for understanding the impact of management practices on retail performance are developed under the assumption of stability, equilibrium and linearity, whereas retail operations are considered in reality to be dynamic, non-linear and complex. Alternatively, discrete event and agent-based modelling... |
Title: Distributed Autonomous Online Learning: Regrets and Intrinsic Privacy-Preserving Properties |
Abstract: Online learning has become increasingly popular on handling massive data. The sequential nature of online learning, however, requires a centralized learner to store data and update parameters. In this paper, we consider online learning with \em distributed data sources. The autonomous learners update local pa... |
Title: Online Identification and Tracking of Subspaces from Highly Incomplete Information |
Abstract: This work presents GROUSE (Grassmanian Rank-One Update Subspace Estimation), an efficient online algorithm for tracking subspaces from highly incomplete observations. GROUSE requires only basic linear algebraic manipulations at each iteration, and each subspace update can be performed in linear time in the di... |
Title: Optimization of Weighted Curvature for Image Segmentation |
Abstract: Minimization of boundary curvature is a classic regularization technique for image segmentation in the presence of noisy image data. Techniques for minimizing curvature have historically been derived from descent methods which could be trapped in a local minimum and therefore required a good initialization. R... |
Title: Large gaps imputation in remote sensed imagery of the environment |
Abstract: Imputation of missing data in large regions of satellite imagery is necessary when the acquired image has been damaged by shadows due to clouds, or information gaps produced by sensor failure. The general approach for imputation of missing data, that could not be considered missed at random, suggests the use ... |
Title: Stochastic Search with an Observable State Variable |
Abstract: In this paper we study convex stochastic search problems where a noisy objective function value is observed after a decision is made. There are many stochastic search problems whose behavior depends on an exogenous state variable which affects the shape of the objective function. Currently, there is no genera... |
Title: A Statistical Social Network Model for Consumption Data in Food Webs |
Abstract: We adapt existing statistical modeling techniques for social networks to study consumption data observed in trophic food webs. These data describe the feeding volume (non-negative) among organisms grouped into nodes, called trophic species, that form the food web. Model complexity arises due to the extensive ... |
Title: On the Implementation of the Probabilistic Logic Programming Language ProbLog |
Abstract: The past few years have seen a surge of interest in the field of probabilistic logic learning and statistical relational learning. In this endeavor, many probabilistic logics have been developed. ProbLog is a recent probabilistic extension of Prolog motivated by the mining of large biological networks. In Pro... |
Title: sTeX+ - a System for Flexible Formalization of Linked Data |
Abstract: We present the sTeX+ system, a user-driven advancement of sTeX - a semantic extension of LaTeX that allows for producing high-quality PDF documents for (proof)reading and printing, as well as semantic XML/OMDoc documents for the Web or further processing. Originally sTeX had been created as an invasive, seman... |
Title: A Novel Rough Set Reduct Algorithm for Medical Domain Based on Bee Colony Optimization |
Abstract: Feature selection refers to the problem of selecting relevant features which produce the most predictive outcome. In particular, feature selection task is involved in datasets containing huge number of features. Rough set theory has been one of the most successful methods used for feature selection. However, ... |
Title: Human Disease Diagnosis Using a Fuzzy Expert System |
Abstract: Human disease diagnosis is a complicated process and requires high level of expertise. Any attempt of developing a web-based expert system dealing with human disease diagnosis has to overcome various difficulties. This paper describes a project work aiming to develop a web-based fuzzy expert system for diagno... |
Title: Vagueness of Linguistic variable |
Abstract: In the area of computer science focusing on creating machines that can engage on behaviors that humans consider intelligent. The ability to create intelligent machines has intrigued humans since ancient times and today with the advent of the computer and 50 years of research into various programming technique... |
Title: Evolution of Biped Walking Using Neural Oscillators Controller and Harmony Search Algorithm Optimizer |
Abstract: In this paper, a simple Neural controller has been used to achieve stable walking in a NAO biped robot, with 22 degrees of freedom that implemented in a virtual physics-based simulation environment of Robocup soccer simulation environment. The algorithm uses a Matsuoka base neural oscillator to generate contr... |
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