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ICML
2008
IEEE
14 years 8 months ago
Optimizing estimated loss reduction for active sampling in rank learning
Learning to rank is becoming an increasingly popular research area in machine learning. The ranking problem aims to induce an ordering or preference relations among a set of insta...
Pinar Donmez, Jaime G. Carbonell
GECCO
2009
Springer
14 years 2 months ago
How novelty search escapes the deceptive trap of learning to learn
Sebastian Risi, Sandy D. Vanderbleek, Charles E. H...
ICONIP
2004
13 years 9 months ago
Evaluation of Comprehensive Learning Particle Swarm Optimizer
Abstract. Particle Swarm Optimizer (PSO) is one of the evolutionary computation techniques based on swarm intelligence. Comprehensive Learning Particle Swarm Optimizer (CLPSO) is a...
Jing J. Liang, A. Kai Qin, Ponnuthurai N. Sugantha...
ALDT
2009
Springer
207views Algorithms» more  ALDT 2009»
14 years 2 months ago
Anytime Self-play Learning to Satisfy Functional Optimality Criteria
We present an anytime multiagent learning approach to satisfy any given optimality criterion in repeated game self-play. Our approach is opposed to classical learning approaches fo...
Andriy Burkov, Brahim Chaib-draa
GECCO
2007
Springer
149views Optimization» more  GECCO 2007»
14 years 1 months ago
Learning classifier systems
Martin V. Butz