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» Dirichlet Process Mixtures of Generalized Linear Models
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192
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ICASSP
2011
IEEE
14 years 11 months ago
Blind separation of multiple binary sources from one nonlinear mixture
We propose a new method for the blind separation of multiple binary signals from a single general nonlinear mixture. In addition to the usual independence assumption on the input ...
Konstantinos I. Diamantaras, Theophilos Papadimitr...
ACL
2012
13 years 9 months ago
A Nonparametric Bayesian Approach to Acoustic Model Discovery
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
Chia-ying Lee, James R. Glass
198
Voted
FLAIRS
2010
15 years 9 months ago
Generalized Non-impeding Noisy-AND Trees
To specify a Bayes net (BN), a conditional probability table (CPT), often of an effect conditioned on its n causes, needs assessed for each node. Its complexity is generally expon...
Yang Xiang
ICA
2007
Springer
15 years 11 months ago
Underdetermined Source Separation Using Mixtures of Warped Laplacians
In a previous work, the authors have introduced a Mixture of Laplacians model in order to cluster the observed data into the sound sources that exist in an underdetermined two-sens...
Nikolaos Mitianoudis, Tania Stathaki
225
Voted
NIPS
2004
15 years 8 months ago
Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution
Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in ima...
Hyun-Jin Park, Te-Won Lee