219 search results - page 15 / 44 » Using Markov Blankets for Causal Structure Learning |
152
Voted
ICASSP
2011
IEEE
14 years 7 months ago
2011
IEEE
We present a semi-supervised source separation methodology to denoise speech by modeling speech as one source and noise as the other source. We model speech using the recently pro...
116
Voted
UAI
1998
15 years 5 months ago
1998
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
114
Voted
ICPR
2008
IEEE
15 years 10 months ago
2008
IEEE
In patch based face super-resolution method, the patch size is usually very small, and neighbor patches’ relationship via overlapped regions is only to keep smoothness of recons...
154
Voted
ICML
2008
IEEE
16 years 4 months ago
2008
IEEE
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
124
Voted
ICML
2008
IEEE
16 years 4 months ago
2008
IEEE
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...