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» On the Complexity of Train Assignment Problems
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NIPS
2004
15 years 5 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
ACL
2010
15 years 1 months ago
Starting from Scratch in Semantic Role Labeling
A fundamental step in sentence comprehension involves assigning semantic roles to sentence constituents. To accomplish this, the listener must parse the sentence, find constituent...
Michael Connor, Yael Gertner, Cynthia Fisher, Dan ...
GECCO
2006
Springer
164views Optimization» more  GECCO 2006»
15 years 7 months ago
Adaptation for parallel memetic algorithm based on population entropy
In this paper, we propose the island model parallel memetic algorithm with diversity-based dynamic adaptive strategy (PMADLS) for controlling the local search frequency and demons...
Jing Tang, Meng-Hiot Lim, Yew-Soon Ong
COCOA
2008
Springer
15 years 5 months ago
Parameterized Graph Editing with Chosen Vertex Degrees
We study the parameterized complexity of the following problem: is it possible to make a given graph r-regular by applying at most k elementary editing operations; the operations a...
Luke Mathieson, Stefan Szeider
EMNLP
2007
15 years 5 months ago
A Constraint Satisfaction Approach to Dependency Parsing
We present an adaptation of constraint satisfaction inference (Canisius et al., 2006b) for predicting dependency trees. Three different classifiers are trained to predict weighte...
Sander Canisius, Erik Tjong Kim Sang