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EMNLP
2010
13 years 6 months ago
Efficient Graph-Based Semi-Supervised Learning of Structured Tagging Models
We describe a new scalable algorithm for semi-supervised training of conditional random fields (CRF) and its application to partof-speech (POS) tagging. The algorithm uses a simil...
Amarnag Subramanya, Slav Petrov, Fernando Pereira
CVPR
2004
IEEE
14 years 10 months ago
Graphical Models for Graph Matching
This paper explores a formulation for attributed graph matching as an inference problem over a hidden Markov Random Field. We approximate the fully connected model with simpler mo...
Dante Augusto Couto Barone, Terry Caelli, Tib&eacu...
JCT
2007
117views more  JCT 2007»
13 years 8 months ago
Large independent sets in regular graphs of large girth
Let G be a d-regular graph with girth g, and let α be the independence number of G. We show that α(G) ≥ 1 2 1 − (d − 1)−2/(d−2) − (g) n where (g) → 0 as g → ∞,...
Joseph Lauer, Nicholas C. Wormald
FOCI
2007
IEEE
14 years 2 months ago
Faster Evolutionary Algorithms by Superior Graph Representation
— We present a new representation for individuals in problems that have cyclic permutations as solutions. To demonstrate its usefulness, we analyze a simple randomized local sear...
Benjamin Doerr, Christian Klein, Tobias Storch
DAGM
2008
Springer
13 years 10 months 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