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» Mixtures of Gaussian Processes
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FOCS
1999
IEEE
13 years 11 months ago
Learning Mixtures of Gaussians
Mixtures of Gaussians are among the most fundamental and widely used statistical models. Current techniques for learning such mixtures from data are local search heuristics with w...
Sanjoy Dasgupta
NIPS
2001
13 years 8 months ago
Covariance Kernels from Bayesian Generative Models
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
Matthias Seeger
SAC
2011
ACM
13 years 1 months ago
Slice sampling mixture models
We propose a more efficient version of the slice sampler for Dirichlet process mixture models described by Walker (2007). This sampler allows the fitting of infinite mixture mod...
Maria Kalli, Jim E. Griffin, Stephen G. Walker
NPL
2002
140views more  NPL 2002»
13 years 6 months ago
A Greedy EM Algorithm for Gaussian Mixture Learning
Learninga Gaussian mixturewithalocal algorithm like EMcanbe dif
Nikos A. Vlassis, Aristidis Likas
ICASSP
2011
IEEE
12 years 10 months ago
Improving melody extraction using Probabilistic Latent Component Analysis
We propose a new approach for automatic melody extraction from polyphonic audio, based on Probabilistic Latent Component Analysis (PLCA). An audio signal is first divided into vo...
Jinyu Han, Ching-Wei Chen