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ACL
2008
13 years 10 months ago
Semi-Supervised Convex Training for Dependency Parsing
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
Qin Iris Wang, Dale Schuurmans, Dekang Lin
ICML
2006
IEEE
14 years 10 months ago
Experience-efficient learning in associative bandit problems
We formalize the associative bandit problem framework introduced by Kaelbling as a learning-theory problem. The learning environment is modeled as a k-armed bandit where arm payof...
Alexander L. Strehl, Chris Mesterharm, Michael L. ...
NPC
2007
Springer
14 years 3 months ago
A Cost-Aware Parallel Workload Allocation Approach Based on Machine Learning Techniques
Parallelism is one of the main sources for performance improvement in modern computing environment, but the efficient exploitation of the available parallelism depends on a number ...
Shun Long, Grigori Fursin, Björn Franke
COLT
2010
Springer
13 years 7 months ago
Active Learning on Trees and Graphs
We investigate the problem of active learning on a given tree whose nodes are assigned binary labels in an adversarial way. Inspired by recent results by Guillory and Bilmes, we c...
Nicolò Cesa-Bianchi, Claudio Gentile, Fabio...
BMCBI
2008
153views more  BMCBI 2008»
13 years 9 months ago
AWclust: point-and-click software for non-parametric population structure analysis
Background: Population structure analysis is important to genetic association studies and evolutionary investigations. Parametric approaches, e.g. STRUCTURE and L-POP, usually ass...
Xiaoyi Gao, Joshua D. Starmer