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CVPR
2007
IEEE
16 years 8 months ago
Utilizing Variational Optimization to Learn Markov Random Fields
Markov Random Field, or MRF, models are a powerful tool for modeling images. While much progress has been made in algorithms for inference in MRFs, learning the parameters of an M...
Marshall F. Tappen
SSIAI
2000
IEEE
15 years 11 months ago
Pairwise Markov Random Fields and its Application in Textured Images Segmentation
The use of random fields, which allows one to take into account the spatial interaction among random variables in complex systems, is a frequent tool in numerous problems of stati...
Wojciech Pieczynski, Abdel-Nasser Tebbache
PVLDB
2010
103views more  PVLDB 2010»
15 years 5 months ago
Probabilistic XML via Markov Chains
We show how Recursive Markov Chains (RMCs) and their restrictions can define probabilistic distributions over XML documents, and study tractability of querying over such models. ...
Michael Benedikt, Evgeny Kharlamov, Dan Olteanu, P...
NIPS
2008
15 years 8 months ago
Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data
Inspired by the hierarchical hidden Markov models (HHMM), we present the hierarchical semi-Markov conditional random field (HSCRF), a generalisation of embedded undirected Markov ...
Tran The Truyen, Dinh Q. Phung, Hung Hai Bui, Svet...
IJCAI
2003
15 years 8 months ago
A Statistical Model for Flexible String Similarity
This paper proposes a statistical model for defining string similarity. The proposed model is based on hidden Markov model and defines string similarity as the combination of simi...
Atsuhiro Takasu