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Title: A note on convergence of the equi-energy sampler |
Abstract: In a recent paper `The equi-energy sampler with applications statistical inference and statistical mechanics' [Ann. Stat. 34 (2006) 1581--1619], Kou, Zhou & Wong have presented a new stochastic simulation method called the equi-energy (EE) sampler. This technique is designed to simulate from a probability mea... |
Title: Population-Based Reversible Jump Markov Chain Monte Carlo |
Abstract: In this paper we present an extension of population-based Markov chain Monte Carlo (MCMC) to the trans-dimensional case. One of the main challenges in MCMC-based inference is that of simulating from high and trans-dimensional target measures. In such cases, MCMC methods may not adequately traverse the support... |
Title: A Tutorial on Spectral Clustering |
Abstract: In recent years, spectral clustering has become one of the most popular modern clustering algorithms. It is simple to implement, can be solved efficiently by standard linear algebra software, and very often outperforms traditional clustering algorithms such as the k-means algorithm. On the first glance spectr... |
Title: A Geometric Approach to Confidence Sets for Ratios: Fieller's Theorem, Generalizations, and Bootstrap |
Abstract: We present a geometric method to determine confidence sets for the ratio E(Y)/E(X) of the means of random variables X and Y. This method reduces the problem of constructing confidence sets for the ratio of two random variables to the problem of constructing confidence sets for the means of one-dimensional ran... |
Title: Bayesian finite mixtures: a note on prior specification and posterior computation |
Abstract: A new method for the computation of the posterior distribution of the number k of components in a finite mixture is presented. Two aspects of prior specification are also studied: an argument is made for the use of a Poisson(1) distribution as the prior for k; and methods are given for the selection of hyperp... |
Title: Singular Curves in the Joint Space and Cusp Points of 3-RPR parallel manipulators |
Abstract: This paper investigates the singular curves in the joint space of a family of planar parallel manipulators. It focuses on special points, referred to as cusp points, which may appear on these curves. Cusp points play an important role in the kinematic behavior of parallel manipulators since they make possible... |
Title: On the Distribution of Penalized Maximum Likelihood Estimators: The LASSO, SCAD, and Thresholding |
Abstract: We study the distributions of the LASSO, SCAD, and thresholding estimators, in finite samples and in the large-sample limit. The asymptotic distributions are derived for both the case where the estimators are tuned to perform consistent model selection and for the case where the estimators are tuned to perfor... |
Title: Discriminative Phoneme Sequences Extraction for Non-Native Speaker's Origin Classification |
Abstract: In this paper we present an automated method for the classification of the origin of non-native speakers. The origin of non-native speakers could be identified by a human listener based on the detection of typical pronunciations for each nationality. Thus we suppose the existence of several phoneme sequences ... |
Title: Nonparametric Regression, Confidence Regions and Regularization |
Abstract: In this paper we offer a unified approach to the problem of nonparametric regression on the unit interval. It is based on a universal, honest and non-asymptotic confidence region which is defined by a set of linear inequalities involving the values of the functions at the design points. Interest will typicall... |
Title: Performance Bounds for Lambda Policy Iteration and Application to the Game of Tetris |
Abstract: We consider the discrete-time infinite-horizon optimal control problem formalized by Markov Decision Processes. We revisit the work of Bertsekas and Ioffe, that introduced $\lambda$ Policy Iteration, a family of algorithms parameterized by $\lambda$ that generalizes the standard algorithms Value Iteration and... |
Title: Addendum to Research MMMCV; A Man/Microbio/Megabio/Computer Vision |
Abstract: In October 2007, a Research Proposal for the University of Sydney, Australia, the author suggested that biovie-physical phenomenon as `electrodynamic dependant biological vision', is governed by relativistic quantum laws and biovision. The phenomenon on the basis of `biovielectroluminescence', satisfies man/m... |
Title: Combined Acoustic and Pronunciation Modelling for Non-Native Speech Recognition |
Abstract: In this paper, we present several adaptation methods for non-native speech recognition. We have tested pronunciation modelling, MLLR and MAP non-native pronunciation adaptation and HMM models retraining on the HIWIRE foreign accented English speech database. The ``phonetic confusion'' scheme we have developed... |
Title: Infinite Viterbi alignments in the two state hidden Markov models |
Abstract: Since the early days of digital communication, Hidden Markov Models (HMMs) have now been routinely used in speech recognition, processing of natural languages, images, and in bioinformatics. An HMM $(X_i,Y_i)_i\ge 1$ assumes observations $X_1,X_2,...$ to be conditionally independent given an "explanotary" Mar... |
Title: Confidence Sets Based on Sparse Estimators Are Necessarily Large |
Abstract: Confidence sets based on sparse estimators are shown to be large compared to more standard confidence sets, demonstrating that sparsity of an estimator comes at a substantial price in terms of the quality of the estimator. The results are set in a general parametric or semiparametric framework. |
Title: Am\'elioration des Performances des Syst\`emes Automatiques de Reconnaissance de la Parole pour la Parole Non Native |
Abstract: In this article, we present an approach for non native automatic speech recognition (ASR). We propose two methods to adapt existing ASR systems to the non-native accents. The first method is based on the modification of acoustic models through integration of acoustic models from the mother tong. The phonemes ... |
Title: Modeling homophily and stochastic equivalence in symmetric relational data |
Abstract: This article discusses a latent variable model for inference and prediction of symmetric relational data. The model, based on the idea of the eigenvalue decomposition, represents the relationship between two nodes as the weighted inner-product of node-specific vectors of latent characteristics. This ``eigenmo... |
Title: Analytical approach to bit-string models of language evolution |
Abstract: A formulation of bit-string models of language evolution, based on differential equations for the population speaking each language, is introduced and preliminarily studied. Connections with replicator dynamics and diffusion processes are pointed out. The stability of the dominance state, where most of the po... |
Title: Towards a Sound Theory of Adaptation for the Simple Genetic Algorithm |
Abstract: The pace of progress in the fields of Evolutionary Computation and Machine Learning is currently limited -- in the former field, by the improbability of making advantageous extensions to evolutionary algorithms when their capacity for adaptation is poorly understood, and in the latter by the difficulty of fin... |
Title: Instantaneous and lagged measurements of linear and nonlinear dependence between groups of multivariate time series: frequency decomposition |
Abstract: Measures of linear dependence (coherence) and nonlinear dependence (phase synchronization) between any number of multivariate time series are defined. The measures are expressed as the sum of lagged dependence and instantaneous dependence. The measures are non-negative, and take the value zero only when there... |
Title: Predicting relevant empty spots in social interaction |
Abstract: An empty spot refers to an empty hard-to-fill space which can be found in the records of the social interaction, and is the clue to the persons in the underlying social network who do not appear in the records. This contribution addresses a problem to predict relevant empty spots in social interaction. Homoge... |
Title: Inference for stochastic volatility models using time change transformations |
Abstract: We address the problem of parameter estimation for diffusion driven stochastic volatility models through Markov chain Monte Carlo (MCMC). To avoid degeneracy issues we introduce an innovative reparametrisation defined through transformations that operate on the time scale of the diffusion. A novel MCMC scheme... |
Title: Likelihood-based inference for correlated diffusions |
Abstract: We address the problem of likelihood based inference for correlated diffusion processes using Markov chain Monte Carlo (MCMC) techniques. Such a task presents two interesting problems. First, the construction of the MCMC scheme should ensure that the correlation coefficients are updated subject to the positiv... |
Title: Enhancing Sparsity by Reweighted L1 Minimization |
Abstract: It is now well understood that (1) it is possible to reconstruct sparse signals exactly from what appear to be highly incomplete sets of linear measurements and (2) that this can be done by constrained L1 minimization. In this paper, we study a novel method for sparse signal recovery that in many situations o... |
Title: Kinematic calibration of orthoglide-type mechanisms |
Abstract: The paper proposes a novel calibration approach for the Orthoglide-type mechanisms based on observations of the manipulator leg parallelism during mo-tions between the prespecified test postures. It employs a low-cost measuring system composed of standard comparator indicators attached to the universal magnet... |
Title: Building Rules on Top of Ontologies for the Semantic Web with Inductive Logic Programming |
Abstract: Building rules on top of ontologies is the ultimate goal of the logical layer of the Semantic Web. To this aim an ad-hoc mark-up language for this layer is currently under discussion. It is intended to follow the tradition of hybrid knowledge representation and reasoning systems such as $$-log that integrates... |
Title: Dated ancestral trees from binary trait data and its application to the diversification of languages |
Abstract: Binary trait data record the presence or absence of distinguishing traits in individuals. We treat the problem of estimating ancestral trees with time depth from binary trait data. Simple analysis of such data is problematic. Each homology class of traits has a unique birth event on the tree, and the birth ev... |
Title: The Residual Information Criterion, Corrected |
Abstract: Shi and Tsai (JRSSB, 2002) proposed an interesting residual information criterion (RIC) for model selection in regression. Their RIC was motivated by the principle of minimizing the Kullback-Leibler discrepancy between the residual likelihoods of the true and candidate model. We show, however, under this prin... |
Title: Bootstrap Confidence Regions for Optimal Operating Conditions in Response Surface Methodology |
Abstract: This article concerns the application of bootstrap methodology to construct a likelihood-based confidence region for operating conditions associated with the maximum of a response surface constrained to a specified region. Unlike classical methods based on the stationary point, proper interpretation of this c... |
Title: Empirical Evaluation of Four Tensor Decomposition Algorithms |
Abstract: Higher-order tensor decompositions are analogous to the familiar Singular Value Decomposition (SVD), but they transcend the limitations of matrices (second-order tensors). SVD is a powerful tool that has achieved impressive results in information retrieval, collaborative filtering, computational linguistics, ... |
Title: Computer Model of a "Sense of Humour". I. General Algorithm |
Abstract: A computer model of a "sense of humour" is proposed. The humorous effect is interpreted as a specific malfunction in the course of information processing due to the need for the rapid deletion of the false version transmitted into consciousness. The biological function of a sense of humour consists in speedin... |
Title: Computer Model of a "Sense of Humour". II. Realization in Neural Networks |
Abstract: The computer realization of a "sense of humour" requires the creation of an algorithm for solving the "linguistic problem", i.e. the problem of recognizing a continuous sequence of polysemantic images. Such algorithm may be realized in the Hopfield model of a neural network after its proper modification. |
Title: On the Information Rates of the Plenoptic Function |
Abstract: The \it plenoptic function (Adelson and Bergen, 91) describes the visual information available to an observer at any point in space and time. Samples of the plenoptic function (POF) are seen in video and in general visual content, and represent large amounts of information. In this paper we propose a stochast... |
Title: Can a Computer Laugh ? |
Abstract: A computer model of "a sense of humour" suggested previously [arXiv:0711.2058,0711.2061], relating the humorous effect with a specific malfunction in information processing, is given in somewhat different exposition. Psychological aspects of humour are elaborated more thoroughly. The mechanism of laughter is ... |
Title: Models for dependent extremes using stable mixtures |
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