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GECCO
2008
Springer
109views Optimization» more  GECCO 2008»
13 years 8 months ago
Focused no free lunch theorems
Proofs and empirical evidence are presented which show that a subset of algorithms can have identical performance over a subset of functions, even when the subset of functions is ...
Darrell Whitley, Jonathan E. Rowe
PAMI
2012
11 years 9 months ago
Sparse Algorithms Are Not Stable: A No-Free-Lunch Theorem
Abstract—We consider two desired properties of learning algorithms: sparsity and algorithmic stability. Both properties are believed to lead to good generalization ability. We sh...
Huan Xu, Constantine Caramanis, Shie Mannor
GECCO
2006
Springer
137views Optimization» more  GECCO 2006»
13 years 11 months ago
Structure and metaheuristics
Metaheuristics have often been shown to be effective for difficult combinatorial optimization problems. The reason for that, however, remains unclear. A framework for a theory of ...
Yossi Borenstein, Riccardo Poli
AUSAI
2005
Springer
13 years 9 months ago
A Comparison of Evolutionary Methods for the Discovery of Local Search Heuristics
Abstract. Methods of adaptive constraint satisfaction have recently become of interest to overcome the limitations imposed on “black-box” search algorithms by the no free lunch...
Stuart Bain, John Thornton, Abdul Sattar