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JMLR
2010
141views more  JMLR 2010»
13 years 3 months ago
Hierarchical Gaussian Process Regression
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
Sunho Park, Seungjin Choi
TASLP
2010
101views more  TASLP 2010»
13 years 3 months ago
Gaussian Model-Based Multichannel Speech Presence Probability
The knowledge of the target speech presence probability in a mixture of signals captured by a speech communication system is of paramount importance in several applications includi...
Mehrez Souden, Jingdong Chen, Jacob Benesty, Sofi&...
TSP
2010
13 years 3 months ago
Covariance estimation in decomposable Gaussian graphical models
Graphical models are a framework for representing and exploiting prior conditional independence structures within distributions using graphs. In the Gaussian case, these models are...
Ami Wiesel, Yonina C. Eldar, Alfred O. Hero
TSP
2010
13 years 3 months ago
Joint nonlinear channel equalization and soft LDPC decoding with Gaussian processes
In this paper, we introduce a new approach for nonlinear equalization based on Gaussian processes for classification (GPC). We propose to measure the performance of this equalizer ...
Pablo M. Olmos, Juan José Murillo-Fuentes, ...
TSP
2010
13 years 3 months ago
Gaussian multiresolution models: exploiting sparse Markov and covariance structure
We consider the problem of learning Gaussian multiresolution (MR) models in which data are only available at the finest scale and the coarser, hidden variables serve both to captu...
Myung Jin Choi, Venkat Chandrasekaran, Alan S. Wil...