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» Rate-Distortion via Markov Chain Monte Carlo
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ICA
2007
Springer
15 years 1 months ago
Infinite Sparse Factor Analysis and Infinite Independent Components Analysis
Abstract. A nonparametric Bayesian extension of Independent Components Analysis (ICA) is proposed where observed data Y is modelled as a linear superposition, G, of a potentially i...
David Knowles, Zoubin Ghahramani
AUSAI
2006
Springer
15 years 1 months ago
Learning Hybrid Bayesian Networks by MML
Abstract. We use a Markov Chain Monte Carlo (MCMC) MML algorithm to learn hybrid Bayesian networks from observational data. Hybrid networks represent local structure, using conditi...
Rodney T. O'Donnell, Lloyd Allison, Kevin B. Korb
60
Voted
WSC
2007
14 years 12 months ago
Transformations for accelerating MCMC simulations with broken ergodicity
A new approach for overcoming broken ergodicity in Markov Chain Monte Carlo (MCMC) simulations of complex systems is described. The problem of broken ergodicity is often present i...
Mark Fleischer
CORR
2008
Springer
107views Education» more  CORR 2008»
14 years 9 months ago
Estimating Signals with Finite Rate of Innovation from Noisy Samples: A Stochastic Algorithm
As an example of the recently introduced concept of rate of innovation, signals that are linear combinations of a finite number of Diracs per unit time can be acquired by linear fi...
Vincent Yan Fu Tan, Vivek K. Goyal
71
Voted
CSDA
2006
87views more  CSDA 2006»
14 years 9 months ago
Choice of B-splines with free parameters in the flexible discriminant analysis context
Flexible discriminant analysis (FDA) is a general methodology which aims at providing tools for multigroup non linear classification. It consists in a nonparametric version of dis...
Christelle Reynès, Robert Sabatier, Nicolas...