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NIPS
2004
15 years 7 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 4 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 4 months 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»
15 years 1 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 8 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