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CORR
1999
Springer
112views Education» more  CORR 1999»
15 years 6 months ago
Learning Transformation Rules to Find Grammatical Relations
Grammatical relationships are an important level of natural language processing. We present a trainable approach to find these relationships through transformation sequences and-e...
Lisa Ferro, Marc B. Vilain, Alexander S. Yeh
NECO
2010
97views more  NECO 2010»
15 years 5 months ago
Derivatives of Logarithmic Stationary Distributions for Policy Gradient Reinforcement Learning
Most conventional Policy Gradient Reinforcement Learning (PGRL) algorithms neglect (or do not explicitly make use of) a term in the average reward gradient with respect to the pol...
Tetsuro Morimura, Eiji Uchibe, Junichiro Yoshimoto...
ACL
2009
15 years 4 months ago
Learning Semantic Correspondences with Less Supervision
A central problem in grounded language acquisition is learning the correspondences between a rich world state and a stream of text which references that world state. To deal with ...
Percy Liang, Michael I. Jordan, Dan Klein
ICMCS
2009
IEEE
147views Multimedia» more  ICMCS 2009»
15 years 4 months ago
Not all tags are created equal: Learning flickr tag semantics for global annotation
Large collaborative datasets offer the challenging opportunity of creating systems capable of extracting knowledge in the presence of noisy data. In this work we explore the abili...
Emily Moxley, Jim Kleban, Jiejun Xu, B. S. Manjuna...
ACL
2012
13 years 9 months ago
Learning to Find Translations and Transliterations on the Web
In this paper, we present a new method for learning to finding translations and transliterations on the Web for a given term. The approach involves using a small set of terms and ...
Joseph Z. Chang, Jason S. Chang, Jyh-Shing Roger J...