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» Function Optimization with Coevolutionary Algorithms
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CIKM
2008
Springer
15 years 4 months ago
Suppressing outliers in pairwise preference ranking
Many of the recently proposed algorithms for learning feature-based ranking functions are based on the pairwise preference framework, in which instead of taking documents in isola...
Vitor R. Carvalho, Jonathan L. Elsas, William W. C...
127
Voted
CORR
2010
Springer
100views Education» more  CORR 2010»
15 years 2 months ago
Products of Weighted Logic Programs
Abstract. Weighted logic programming, a generalization of bottom-up logic programming, is a successful framework for specifying dynamic programming algorithms. In this setting, pro...
Shay B. Cohen, Robert J. Simmons, Noah A. Smith
112
Voted
CSDA
2006
84views more  CSDA 2006»
15 years 2 months ago
Three-mode partitioning
The three-mode partitioning model is a clustering model for three-way three-mode data sets that implies a simultaneous partitioning of all three modes involved in the data. In the...
Jan Schepers, Iven Van Mechelen, Eva Ceulemans
GECCO
2010
Springer
211views Optimization» more  GECCO 2010»
15 years 3 months ago
Investigating EA solutions for approximate KKT conditions in smooth problems
Evolutionary algorithms (EAs) are increasingly being applied to solve real-parameter optimization problems due to their flexibility in handling complexities such as non-convexity,...
Rupesh Tulshyan, Ramnik Arora, Kalyanmoy Deb, Joyd...
122
Voted
ICML
1998
IEEE
16 years 3 months ago
The MAXQ Method for Hierarchical Reinforcement Learning
This paper presents a new approach to hierarchical reinforcement learning based on the MAXQ decomposition of the value function. The MAXQ decomposition has both a procedural seman...
Thomas G. Dietterich