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JAIR
1998
198views more  JAIR 1998»
9 years 6 months ago
Probabilistic Inference from Arbitrary Uncertainty using Mixtures of Factorized Generalized Gaussians
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
Alberto Ruiz, Pedro E. López-de-Teruel, M. ...
CORR
2016
Springer
71views Education» more  CORR 2016»
4 years 3 months ago
Low-rank Matrix Factorization under General Mixture Noise Distributions
Many computer vision problems can be posed as learning a low-dimensional subspace from high dimensional data. The low rank matrix factorization (LRMF) represents a commonly utiliz...
Xiangyong Cao, Qian Zhao, Deyu Meng, Yang Chen, Zo...
TASLP
2010
117views more  TASLP 2010»
9 years 1 months ago
Speech Enhancement Using Gaussian Scale Mixture Models
This paper presents a novel probabilistic approach to speech enhancement. Instead of a deterministic logarithmic relationship, we assume a probabilistic relationship between the fr...
Jiucang Hao, Te-Won Lee, Terrence J. Sejnowski
ICASSP
2009
IEEE
9 years 10 months ago
Multichannel nonnegative matrix factorization in convolutive mixtures. With application to blind audio source separation
We consider inference in a general data-driven object-based model of multichannel audio data, assumed generated as a possibly underdetermined convolutive mixture of source signals...
Alexey Ozerov, Cédric Févotte
CORR
2010
Springer
160views Education» more  CORR 2010»
9 years 7 months ago
Scalable Probabilistic Databases with Factor Graphs and MCMC
Incorporating probabilities into the semantics of incomplete databases has posed many challenges, forcing systems to sacrifice modeling power, scalability, or treatment of relatio...
Michael L. Wick, Andrew McCallum, Gerome Miklau
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