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ICML
2008
IEEE
16 years 7 months ago
The asymptotics of semi-supervised learning in discriminative probabilistic models
Semi-supervised learning aims at taking advantage of unlabeled data to improve the efficiency of supervised learning procedures. For discriminative models however, this is a chall...
François Yvon, Nataliya Sokolovska, Olivier...
ICML
2010
IEEE
15 years 7 months ago
Convergence, Targeted Optimality, and Safety in Multiagent Learning
This paper introduces a novel multiagent learning algorithm, Convergence with Model Learning and Safety (or CMLeS in short), which achieves convergence, targeted optimality agains...
Doran Chakraborty, Peter Stone
STOC
1994
ACM
128views Algorithms» more  STOC 1994»
15 years 10 months ago
Weakly learning DNF and characterizing statistical query learning using Fourier analysis
We present new results on the well-studied problem of learning DNF expressions. We prove that an algorithm due to Kushilevitz and Mansour [13] can be used to weakly learn DNF form...
Avrim Blum, Merrick L. Furst, Jeffrey C. Jackson, ...
DATE
2005
IEEE
150views Hardware» more  DATE 2005»
16 years 7 days ago
Pueblo: A Modern Pseudo-Boolean SAT Solver
This paper introduces a new SAT solver that integrates logicbased reasoning and integer programming methods to systems of CNF and PB constraints. Its novel features include an eff...
Hossein M. Sheini, Karem A. Sakallah
ACL
2008
15 years 8 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