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130
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ACL
2009
15 years 2 months ago
Reinforcement Learning for Mapping Instructions to Actions
In this paper, we present a reinforcement learning approach for mapping natural language instructions to sequences of executable actions. We assume access to a reward function tha...
S. R. K. Branavan, Harr Chen, Luke S. Zettlemoyer,...
159
Voted
ACL
2011
14 years 8 months ago
Learning Dependency-Based Compositional Semantics
Compositional question answering begins by mapping questions to logical forms, but training a semantic parser to perform this mapping typically requires the costly annotation of t...
Percy Liang, Michael I. Jordan, Dan Klein
209
Voted
ICANN
2011
Springer
14 years 8 months ago
Learning from Multiple Annotators with Gaussian Processes
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...
Perry Groot, Adriana Birlutiu, Tom Heskes
CVPR
2012
IEEE
13 years 7 months ago
Learning shared body plans
We cast the problem of recognizing related categories as a unified learning and structured prediction problem with shared body plans. When provided with detailed annotations of o...
Ian Endres, Vivek Srikumar, Ming-Wei Chang, Derek ...
ICPR
2006
IEEE
16 years 6 months ago
Online Learning of Discriminative Patterns from Unlimited Sequences of Candidates
Recent research in object recognition has demonstrated the advantages of representing objects and scenes through localized patterns such as small image templates. In this paper we...
Ilkka Autio, Jussi T. Lindgren