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COLT
2008
Springer
13 years 10 months ago
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Shai Ben-David, Tyler Lu, Dávid Pál
ML
2002
ACM
100views Machine Learning» more  ML 2002»
13 years 8 months ago
Structure in the Space of Value Functions
Solving in an efficient manner many different optimal control tasks within the same underlying environment requires decomposing the environment into its computationally elemental ...
David J. Foster, Peter Dayan
PKDD
2010
Springer
160views Data Mining» more  PKDD 2010»
13 years 7 months ago
Entropy and Margin Maximization for Structured Output Learning
Abstract. We consider the problem of training discriminative structured output predictors, such as conditional random fields (CRFs) and structured support vector machines (SSVMs)....
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhm...
ACL
2012
11 years 11 months ago
Learning Translation Consensus with Structured Label Propagation
In this paper, we address the issue for learning better translation consensus in machine translation (MT) research, and explore the search of translation consensus from similar, r...
Shujie Liu, Chi-Ho Li, Mu Li, Ming Zhou
ECTEL
2008
Springer
13 years 10 months ago
Towards Accessing Disparate Educational Data in a Single, Unified Manner
Abstract. Educational researchers need to exchange and compare their learnerinteraction data in order to benefit the learning science community as a whole. In order to support this...
Erica Melis, Bruce M. McLaren, Silvana Solomon