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» On learning linear ranking functions for beam search
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ICML
2007
IEEE
14 years 5 months ago
On learning linear ranking functions for beam search
Beam search is used to maintain tractability in large search spaces at the expense of completeness and optimality. We study supervised learning of linear ranking functions for con...
Yuehua Xu, Alan Fern
SIGIR
2004
ACM
13 years 10 months ago
Learning effective ranking functions for newsgroup search
Web communities are web virtual broadcasting spaces where people can freely discuss anything. While such communities function as discussion boards, they have even greater value as...
Wensi Xi, Jesper Lind, Eric Brill
RECSYS
2010
ACM
13 years 2 months ago
List-wise learning to rank with matrix factorization for collaborative filtering
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
Yue Shi, Martha Larson, Alan Hanjalic
ICASSP
2010
IEEE
12 years 11 months ago
Search error risk minimization in Viterbi beam search for speech recognition
This paper proposes a method to optimize Viterbi beam search based on search error risk minimization in large vocabulary continuous speech recognition (LVCSR). Most speech recogni...
Takaaki Hori, Shinji Watanabe, Atsushi Nakamura
ACL
2009
13 years 2 months ago
Exploiting Bilingual Information to Improve Web Search
Web search quality can vary widely across languages, even for the same information need. We propose to exploit this variation in quality by learning a ranking function on bilingua...
Wei Gao, John Blitzer, Ming Zhou, Kam-Fai Wong