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NAACL
2010
14 years 9 months ago
Learning Dense Models of Query Similarity from User Click Logs
The goal of this work is to integrate query similarity metrics as features into a dense model that can be trained on large amounts of query log data, in order to rank query rewrit...
Fabio De Bona, Stefan Riezler, Keith Hall, Massimi...
ICML
2005
IEEE
16 years 19 days ago
Learning to rank using gradient descent
We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
Christopher J. C. Burges, Tal Shaked, Erin Renshaw...
ALT
2008
Springer
15 years 8 months ago
Smooth Boosting for Margin-Based Ranking
We propose a new boosting algorithm for bipartite ranking problems. Our boosting algorithm, called SoftRankBoost, is a modification of RankBoost which maintains only smooth distri...
Jun-ichi Moribe, Kohei Hatano, Eiji Takimoto, Masa...
CORR
2011
Springer
144views Education» more  CORR 2011»
14 years 3 months ago
Rank Aggregation via Nuclear Norm Minimization
The process of rank aggregation is intimately intertwined with the structure of skew-symmetric matrices. We apply recent advances in the theory and algorithms of matrix completion...
David F. Gleich, Lek-Heng Lim
SIGMOD
2005
ACM
164views Database» more  SIGMOD 2005»
15 years 12 months ago
RankSQL: Query Algebra and Optimization for Relational Top-k Queries
This paper introduces RankSQL, a system that provides a systematic and principled framework to support efficient evaluations of ranking (top-k) queries in relational database syst...
Chengkai Li, Kevin Chen-Chuan Chang, Ihab F. Ilyas...