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» Decision rules and decision markets
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NIPS
2007
14 years 11 months ago
Regularized Boost for Semi-Supervised Learning
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
Ke Chen 0001, Shihai Wang
ACL
2006
14 years 11 months ago
From Prosodic Trees to Syntactic Trees
This paper describes an ongoing effort to parse the Hebrew Bible. The parser consults the bracketing information extracted from the cantillation marks of the Masoetic text. We fir...
Andi Wu, Kirk Lowery
ACL
2003
14 years 11 months ago
Discourse Segmentation of Multi-Party Conversation
We present a domain-independent topic segmentation algorithm for multi-party speech. Our feature-based algorithm combines knowledge about content using a text-based algorithm as a...
Michel Galley, Kathleen McKeown, Eric Fosler-Lussi...
ACL
2003
14 years 11 months ago
Deverbal Compound Noun Analysis Based on Lexical Conceptual Structure
This paper proposes a principled approach for analysis of semantic relations between constituents in compound nouns based on lexical semantic structure. One of the difficulties o...
Koichi Takeuchi, Kyo Kageura, Teruo Koyama
NIPS
2004
14 years 11 months ago
Semi-supervised Learning by Entropy Minimization
We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this framework, we motivate minimum entropy regulariza...
Yves Grandvalet, Yoshua Bengio