216 search results - page 8 / 44 » Learning in Gaussian Markov random fields |
168
Voted
JMLR
2008
15 years 3 months ago
2008
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
129
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CVPR
2007
IEEE
16 years 5 months ago
2007
IEEE
This paper presents a novel spatio-temporal Markov random field (MRF) for video denoising. Two main issues are addressed in this paper, namely, the estimation of noise model and t...
133
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ICML
2005
IEEE
16 years 4 months ago
2005
IEEE
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
129
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SIGIR
2009
ACM
15 years 10 months ago
2009
ACM
Recent work in supervised learning of term-based retrieval models has shown significantly improved accuracy can often be achieved via better model estimation [2, 10, 11, 17]. In ...
142
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NIPS
2004
15 years 4 months ago
2004
We describe semi-Markov conditional random fields (semi-CRFs), a conditionally trained version of semi-Markov chains. Intuitively, a semiCRF on an input sequence x outputs a "...