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ICASSP
2009
IEEE
14 years 2 months ago
Sparse source separation from orthogonal mixtures
This paper addresses source separation from a linear mixture under two assumptions: source sparsity and orthogonality of the mixing matrix. We propose efficient sparse separation...
Moshe Mishali, Yonina C. Eldar
SIGIR
2004
ACM
14 years 1 months ago
A two-stage mixture model for pseudo feedback
Pseudo feedback is a commonly used technique to improve information retrieval performance. It assumes a few top-ranked documents to be relevant, and learns from them to improve th...
Tao Tao, ChengXiang Zhai
CSDA
2007
134views more  CSDA 2007»
13 years 7 months ago
Variational approximations in Bayesian model selection for finite mixture distributions
Variational methods for model comparison have become popular in the neural computing/machine learning literature. In this paper we explore their application to the Bayesian analys...
Clare A. McGrory, D. M. Titterington
NECO
1998
119views more  NECO 1998»
13 years 7 months ago
Density Estimation by Mixture Models with Smoothing Priors
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...
Akio Utsugi
ICASSP
2011
IEEE
12 years 11 months ago
Reconstructing completely overlapped notes from musical mixtures
In mixtures of musical sounds, the problem of overlapped harmonics poses a significant challenge to source separation. Common Amplitude Modulation (CAM) is one of the most effect...
Jinyu Han, Bryan Pardo