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WSDM
2010
ACM
129views Data Mining» more  WSDM 2010»
16 years 1 months ago
Early Exit Optimizations for Additive Machine Learned Ranking Systems
Berkant Barla Cambazoglu, Hugo Zaragoza, Olivier C...
PLDI
2003
ACM
15 years 9 months ago
Meta optimization: improving compiler heuristics with machine learning
Compiler writers have crafted many heuristics over the years to approximately solve NP-hard problems efficiently. Finding a heuristic that performs well on a broad range of applic...
Mark Stephenson, Saman P. Amarasinghe, Martin C. M...
IPPS
2007
IEEE
15 years 11 months ago
Optimizing Sorting with Machine Learning Algorithms
The growing complexity of modern processors has made the development of highly efficient code increasingly difficult. Manually developing highly efficient code is usually expen...
Xiaoming Li, María Jesús Garzar&aacu...
GECCO
2007
Springer
137views Optimization» more  GECCO 2007»
15 years 10 months ago
Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case
The focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, t...
Peter A. N. Bosman, Han La Poutré
TEC
2002
133views more  TEC 2002»
15 years 4 months ago
Learning and optimization using the clonal selection principle
The clonal selection principle is used to explain the basic features of an adaptive immune response to an antigenic stimulus. It establishes the idea that only those cells that rec...
Leandro Nunes de Castro, Fernando J. Von Zuben