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» Algorithm Selection using Reinforcement Learning
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ICML
2004
IEEE
16 years 4 months ago
Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5
Text categorization algorithms usually represent documents as bags of words and consequently have to deal with huge numbers of features. Most previous studies found that the major...
Evgeniy Gabrilovich, Shaul Markovitch
ICIP
2002
IEEE
15 years 8 months ago
An iterative algorithm for context selection in adaptive entropy coders
Context-based adaptive entropy coding is an essential feature of modern image compression algorithms; however, the design of these coders is non-trivial due to the balance that mu...
Tong Jin, Jacques Vaisey
ICCBR
2001
Springer
15 years 7 months ago
Meta-case-Based Reasoning: Using Functional Models to Adapt Case-Based Agents
It is useful for an intelligent software agent to be able to adapt to new demands from an environment. Such adaptation can be viewed as a redesign problem; an agent has some origin...
J. William Murdock, Ashok K. Goel
ACL
2010
15 years 1 months ago
Reading between the Lines: Learning to Map High-Level Instructions to Commands
In this paper, we address the task of mapping high-level instructions to sequences of commands in an external environment. Processing these instructions is challenging--they posit...
S. R. K. Branavan, Luke S. Zettlemoyer, Regina Bar...
120
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CIKM
2009
Springer
15 years 9 months ago
Web search result summarization: title selection algorithms and user satisfaction
Eye tracking experiments have shown that titles of Web search results play a crucial role in guiding a user’s search process. We present a machine-learned algorithm that trains ...
Tapas Kanungo, Nadia Ghamrawi, Ki Yuen Kim, Lawren...