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NIPS
2004
15 years 6 months ago
Unsupervised Variational Bayesian Learning of Nonlinear Models
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...
Antti Honkela, Harri Valpola
AAAI
1997
15 years 6 months ago
Model Minimization in Markov Decision Processes
Many stochastic planning problems can be represented using Markov Decision Processes (MDPs). A difficulty with using these MDP representations is that the common algorithms for so...
Thomas Dean, Robert Givan
COMPGEOM
1998
ACM
15 years 9 months ago
Geometric Applications of a Randomized Optimization Technique
Abstract. We propose a simple, general, randomized technique to reduce certain geometric optimization problems to their corresponding decision problems. These reductions increase t...
Timothy M. Chan
ICASSP
2011
IEEE
14 years 8 months ago
Score informed audio source separation using a parametric model of non-negative spectrogram
In this paper we present a new technique for monaural source separation in musical mixtures, which uses the knowledge of the musical score. This information is used to initialize ...
Romain Hennequin, Bertrand David, Roland Badeau
111
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NIPS
1998
15 years 6 months ago
Convergence of the Wake-Sleep Algorithm
The W-S (Wake-Sleep) algorithm is a simple learning rule for the models with hidden variables. It is shown that this algorithm can be applied to a factor analysis model which is a...
Shiro Ikeda, Shun-ichi Amari, Hiroyuki Nakahara