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Title: Deceptiveness and Neutrality - the ND family of fitness landscapes |
Abstract: When a considerable number of mutations have no effects on fitness values, the fitness landscape is said neutral. In order to study the interplay between neutrality, which exists in many real-world applications, and performances of metaheuristics, it is useful to design landscapes which make it possible to tu... |
Title: Model-Based Event Detection in Wireless Sensor Networks |
Abstract: In this paper we present an application of techniques from statistical signal processing to the problem of event detection in wireless sensor networks used for environmental monitoring. The proposed approach uses the well-established Principal Component Analysis (PCA) technique to build a compact model of the... |
Title: Du corpus au dictionnaire |
Abstract: In this article, we propose an automatic process to build multi-lingual lexico-semantic resources. The goal of these resources is to browse semantically textual information contained in texts of different languages. This method uses a mathematical model called Atlas s\'emantiques in order to represent the dif... |
Title: Mining for adverse drug events with formal concept analysis |
Abstract: The pharmacovigilance databases consist of several case reports involving drugs and adverse events (AEs). Some methods are applied consistently to highlight all signals, i.e. all statistically significant associations between a drug and an AE. These methods are appropriate for verification of more complex rel... |
Title: Cross-situational and supervised learning in the emergence of communication |
Abstract: Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two types of learning algorithms: cross-situational learning, in which the individuals determ... |
Title: Practical Robust Estimators for the Imprecise Dirichlet Model |
Abstract: Walley's Imprecise Dirichlet Model (IDM) for categorical i.i.d. data extends the classical Dirichlet model to a set of priors. It overcomes several fundamental problems which other approaches to uncertainty suffer from. Yet, to be useful in practice, one needs efficient ways for computing the imprecise=robust... |
Title: Google distance between words |
Abstract: Cilibrasi and Vitanyi have demonstrated that it is possible to extract the meaning of words from the world-wide web. To achieve this, they rely on the number of webpages that are found through a Google search containing a given word and they associate the page count to the probability that the word appears on... |
Title: Fixing Convergence of Gaussian Belief Propagation |
Abstract: Gaussian belief propagation (GaBP) is an iterative message-passing algorithm for inference in Gaussian graphical models. It is known that when GaBP converges it converges to the correct MAP estimate of the Gaussian random vector and simple sufficient conditions for its convergence have been established. In th... |
Title: A mixture of experts model for rank data with applications in election studies |
Abstract: A voting bloc is defined to be a group of voters who have similar voting preferences. The cleavage of the Irish electorate into voting blocs is of interest. Irish elections employ a ``single transferable vote'' electoral system; under this system voters rank some or all of the electoral candidates in order of... |
Title: Discretization-invariant Bayesian inversion and Besov space priors |
Abstract: Bayesian solution of an inverse problem for indirect measurement $M = AU + $ is considered, where $U$ is a function on a domain of $R^d$. Here $A$ is a smoothing linear operator and $ $ is Gaussian white noise. The data is a realization $m_k$ of the random variable $M_k = P_kA U+P_k $, where $P_k$ is a linear... |
Title: Geospatial semantics: beyond ontologies, towards an enactive approach |
Abstract: Current approaches to semantics in the geospatial domain are mainly based on ontologies, but ontologies, since continue to build entirely on the symbolic methodology, suffers from the classical problems, e.g. the symbol grounding problem, affecting representational theories. We claim for an enactive approach ... |
Title: Extracting Spooky-activation-at-a-distance from Considerations of Entanglement |
Abstract: Following an early claim by Nelson & McEvoy suggesting that word associations can display `spooky action at a distance behaviour', a serious investigation of the potentially quantum nature of such associations is currently underway. This paper presents a simple quantum model of a word association system. It i... |
Title: Physarum boats: If plasmodium sailed it would never leave a port |
Abstract: Plasmodium of is a single huge (visible by naked eye) cell with myriad of nuclei. The plasmodium is a promising substrate for non-classical, nature-inspired, computing devices. It is capable for approximation of shortest path, computation of planar proximity graphs and plane tessellations, primitive memory an... |
Title: Bayesian projection approaches to variable selection and exploring model uncertainty |
Abstract: A Bayesian approach to variable selection which is based on the expected Kullback-Leibler divergence between the full model and its projection onto a submodel has recently been suggested in the literature. Here we extend this idea by considering projections onto subspaces defined via some form of $L_1$ constr... |
Title: A structural model on a hypercube represented by optimal transport |
Abstract: We propose a flexible statistical model for high-dimensional quantitative data on a hypercube. Our model, called the structural gradient model (SGM), is based on a one-to-one map on the hypercube that is a solution for an optimal transport problem. As we show with many examples, SGM can describe various depen... |
Title: Estimation of Gaussian mixtures in small sample studies using $l_1$ penalization |
Abstract: Many experiments in medicine and ecology can be conveniently modeled by finite Gaussian mixtures but face the problem of dealing with small data sets. We propose a robust version of the estimator based on self-regression and sparsity promoting penalization in order to estimate the components of Gaussian mixtu... |
Title: A Knowledge Discovery Framework for Learning Task Models from User Interactions in Intelligent Tutoring Systems |
Abstract: Domain experts should provide relevant domain knowledge to an Intelligent Tutoring System (ITS) so that it can guide a learner during problemsolving learning activities. However, for many ill-defined domains, the domain knowledge is hard to define explicitly. In previous works, we showed how sequential patter... |
Title: On the Entropy of Written Spanish |
Abstract: This paper reports on results on the entropy of the Spanish language. They are based on an analysis of natural language for n-word symbols (n = 1 to 18), trigrams, digrams, and characters. The results obtained in this work are based on the analysis of twelve different literary works in Spanish, as well as a 2... |
Title: Non-Confluent NLC Graph Grammar Inference by Compressing Disjoint Subgraphs |
Abstract: Grammar inference deals with determining (preferable simple) models/grammars consistent with a set of observations. There is a large body of research on grammar inference within the theory of formal languages. However, there is surprisingly little known on grammar inference for graph grammars. In this paper w... |
Title: Birnbaum-Saunders nonlinear regression models |
Abstract: We introduce, for the first time, a new class of Birnbaum-Saunders nonlinear regression models potentially useful in lifetime data analysis. The class generalizes the regression model described by Rieck and Nedelman [1991, A log-linear model for the Birnbaum-Saunders distribution, Technometrics, 33, 51-60]. W... |
Title: A Keygraph Classification Framework for Real-Time Object Detection |
Abstract: In this paper, we propose a new approach for keypoint-based object detection. Traditional keypoint-based methods consist in classifying individual points and using pose estimation to discard misclassifications. Since a single point carries no relational features, such methods inherently restrict the usage of ... |
Title: How Emotional Mechanism Helps Episodic Learning in a Cognitive Agent |
Abstract: In this paper we propose the CTS (Concious Tutoring System) technology, a biologically plausible cognitive agent based on human brain functions.This agent is capable of learning and remembering events and any related information such as corresponding procedures, stimuli and their emotional valences. Our propo... |
Title: Cut-Simulation and Impredicativity |
Abstract: We investigate cut-elimination and cut-simulation in impredicative (higher-order) logics. We illustrate that adding simple axioms such as Leibniz equations to a calculus for an impredicative logic -- in our case a sequent calculus for classical type theory -- is like adding cut. The phenomenon equally applies... |
Title: Fixed Point Iteration for Estimating The Parameters of Extreme Value Distributions |
Abstract: Maximum likelihood estimations for the parameters of extreme value distributions are discussed in this paper using fixed point iteration. The commonly used numerical approach for addressing this problem is the Newton-Raphson approach which requires differentiation unlike the fixed point iteration which is als... |
Title: Over-enhancement Reduction in Local Histogram Equalization using its Degrees of Freedom |
Abstract: A well-known issue of local (adaptive) histogram equalization (LHE) is over-enhancement (i.e., generation of spurious details) in homogenous areas of the image. In this paper, we show that the LHE problem has many solutions due to the ambiguity in ranking pixels with the same intensity. The LHE solution space... |
Title: An Active Set Algorithm to Estimate Parameters in Generalized Linear Models with Ordered Predictors |
Abstract: In biomedical studies, researchers are often interested in assessing the association between one or more ordinal explanatory variables and an outcome variable, at the same time adjusting for covariates of any type. The outcome variable may be continuous, binary, or represent censored survival times. In the ab... |
Title: Tree Exploration for Bayesian RL Exploration |
Abstract: Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, where optimality improves with increased computational time. This is because the resulting planning task takes the form of a dynamic... |
Title: On the Permutation Distribution of Independence Tests |
Abstract: One of the most popular class of tests for independence between two random variables is the general class of rank statistics which are invariant under permutations. This class contains Spearman's coefficient of rank correlation statistic, Fisher-Yates statistic, weighted Mann statistic and others. Under the n... |
Title: AxialGen: A Research Prototype for Automatically Generating the Axial Map |
Abstract: AxialGen is a research prototype for automatically generating the axial map, which consists of the least number of the longest visibility lines (or axial lines) for representing individual linearly stretched parts of open space of an urban environment. Open space is the space between closed spaces such as bui... |
Title: asympTest: an R package for performing parametric statistical tests and confidence intervals based on the central limit theorem |
Abstract: This paper describes an R package implementing large sample tests and confidence intervals (based on the central limit theorem) for various parameters. The one and two sample mean and variance contexts are considered. The statistics for all the tests are expressed in the same form, which facilitates their pre... |
Title: Graphical Reasoning in Compact Closed Categories for Quantum Computation |
Abstract: Compact closed categories provide a foundational formalism for a variety of important domains, including quantum computation. These categories have a natural visualisation as a form of graphs. We present a formalism for equational reasoning about such graphs and develop this into a generic proof system with a... |
Title: Reconstruction of Epsilon-Machines in Predictive Frameworks and Decisional States |
Abstract: This article introduces both a new algorithm for reconstructing epsilon-machines from data, as well as the decisional states. These are defined as the internal states of a system that lead to the same decision, based on a user-provided utility or pay-off function. The utility function encodes some a priori kn... |
Title: Beyond Zipf's law: Modeling the structure of human language |
Abstract: Human language, the most powerful communication system in history, is closely associated with cognition. Written text is one of the fundamental manifestations of language, and the study of its universal regularities can give clues about how our brains process information and how we, as a society, organize and... |
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