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NIPS
2004
15 years 4 months ago
Semi-Markov Conditional Random Fields for Information Extraction
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 "...
Sunita Sarawagi, William W. Cohen
ECCV
2010
Springer
15 years 1 months ago
Archive Film Restoration Based on Spatiotemporal Random Walks
Abstract. We propose a novel restoration method for defects and missing regions in video sequences, particularly in application to archive film restoration. Our statistical framew...
Xiaosong Wang, Majid Mirmehdi
EMNLP
2009
15 years 29 days ago
On the Use of Virtual Evidence in Conditional Random Fields
Virtual evidence (VE), first introduced by (Pearl, 1988), provides a convenient way of incorporating prior knowledge into Bayesian networks. This work generalizes the use of VE to...
Xiao Li
IJAMCIGI
2010
94views more  IJAMCIGI 2010»
14 years 10 months ago
A Study of Tabu Search for Coloring Random 3-Colorable Graphs Around the Phase Transition
We present an experimental investigation of tabu search (TS) to solve the 3-coloring problem (3-COL). Computational results reveal that a basic TS algorithm is able to find proper ...
Jean-Philippe Hamiez, Jin-Kao Hao, Fred W. Glover
CVPR
1998
IEEE
16 years 5 months ago
Markov Random Fields with Efficient Approximations
Markov Random Fields (MRF's) can be used for a wide variety of vision problems. In this paper we focus on MRF's with two-valued clique potentials, which form a generaliz...
Yuri Boykov, Olga Veksler, Ramin Zabih