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GECCO
2007
Springer
213views Optimization» more  GECCO 2007»
14 years 1 months ago
Genetically programmed learning classifier system description and results
An agent population can be evolved in a complex environment to perform various tasks and optimize its job performance using Learning Classifier System (LCS) technology. Due to the...
Gregory Anthony Harrison, Eric W. Worden
PLDI
2003
ACM
14 years 27 days ago
A provably sound TAL for back-end optimization
Typed assembly languages provide a way to generate machinecheckable safety proofs for machine-language programs. But the soundness proofs of most existing typed assembly languages...
Juan Chen, Dinghao Wu, Andrew W. Appel, Hai Fang
ACMMSP
2006
ACM
260views Hardware» more  ACMMSP 2006»
14 years 1 months ago
Seven at one stroke: results from a cache-oblivious paradigm for scalable matrix algorithms
A blossoming paradigm for block-recursive matrix algorithms is presented that, at once, attains excellent performance measured by • time, • TLB misses, • L1 misses, • L2 m...
Michael D. Adams, David S. Wise
GECCO
2007
Springer
195views Optimization» more  GECCO 2007»
14 years 1 months ago
MILCS: a mutual information learning classifier system
This paper introduces a new variety of learning classifier system (LCS), called MILCS, which utilizes mutual information as fitness feedback. Unlike most LCSs, MILCS is specifical...
Robert Elliott Smith, Max Kun Jiang
CIKM
2005
Springer
14 years 1 months ago
Optimizing candidate check costs for bitmap indices
In this paper, we propose a new strategy for optimizing the placement of bin boundaries to minimize the cost of query evaluation using bitmap indices with binning. For attributes ...
Doron Rotem, Kurt Stockinger, Kesheng Wu