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» Incremental Construction of Structured Hidden Markov Models
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TCBB
2011
13 years 5 months ago
Semantics and Ambiguity of Stochastic RNA Family Models
Stochastic models such as hidden Markov models or stochastic context free grammars can fail to return the correct, maximum likelihood solution in the case of semantic ambiguity. T...
Robert Giegerich, Christian Höner zu Siederdi...
CVPR
2004
IEEE
15 years 13 days ago
A Graphical Model Framework for Coupling MRFs and Deformable Models
This paper proposes a new framework for image segmentation based on the integration of MRFs and deformable models using graphical models. We first construct a graphical model to r...
Rui Huang, Vladimir Pavlovic, Dimitris N. Metaxas
ICASSP
2008
IEEE
14 years 4 months ago
Discriminative training by iterative linear programming optimization
In this paper, we cast discriminative training problems into standard linear programming (LP) optimization. Besides being convex and having globally optimal solution(s), LP progra...
Brian Mak, Benny Ng
TASLP
2002
84views more  TASLP 2002»
13 years 10 months ago
Substate tying with combined parameter training and reduction in tied-mixture HMM design
Two approaches are proposed for the design of tied-mixture hidden Markov models (TMHMM). One approach improves parameter sharing via partial tying of TMHMM states. To facilitate ty...
Liang Gu, Kenneth Rose
DAGM
2008
Springer
14 years 6 days ago
MAP-Inference for Highly-Connected Graphs with DC-Programming
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
Jörg H. Kappes, Christoph Schnörr