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ACL
2011
14 years 10 months ago
Jointly Learning to Extract and Compress
We learn a joint model of sentence extraction and compression for multi-document summarization. Our model scores candidate summaries according to a combined linear model whose fea...
Taylor Berg-Kirkpatrick, Dan Gillick, Dan Klein
ISNN
2007
Springer
16 years 28 days ago
Extensions of Manifold Learning Algorithms in Kernel Feature Space
Manifold learning algorithms have been proven to be capable of discovering some nonlinear structures. However, it is hard for them to extend to test set directly. In this paper, a ...
Yaoliang Yu, Peng Guan, Liming Zhang
IEEEICCI
2002
IEEE
15 years 11 months ago
Quasi-Morphism and Comprehensibility of Rules in Inductive Learning
We present a model of creating a hierarchical set of rules that encode generalizations and exceptions derived from induction learning. The rules use the input features directly an...
Wiphada Wettayaprasit, Chidchanok Lursinsap, Chee-...
AAAI
2008
15 years 9 months ago
Potential-based Shaping in Model-based Reinforcement Learning
Potential-based shaping was designed as a way of introducing background knowledge into model-free reinforcement-learning algorithms. By identifying states that are likely to have ...
John Asmuth, Michael L. Littman, Robert Zinkov
ACL
2007
15 years 8 months ago
Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus
This paper presents the first empirical results to our knowledge on learning synchronous grammars that generate logical forms. Using statistical machine translation techniques, a...
Yuk Wah Wong, Raymond J. Mooney