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JMLR
2012
13 years 9 months ago
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming
Sparse additive models are families of d-variate functions with the additive decomposition f∗ = ∑j∈S f∗ j , where S is an unknown subset of cardinality s d. In this paper,...
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
182
Voted
KDD
2006
ACM
213views Data Mining» more  KDD 2006»
16 years 7 months ago
Learning sparse metrics via linear programming
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
Glenn Fung, Rómer Rosales
GECCO
2009
Springer
142views Optimization» more  GECCO 2009»
15 years 11 months ago
Benchmarking the (1+1)-CMA-ES on the BBOB-2009 noisy testbed
We benchmark an independent-restart-(1+1)-CMA-ES on the BBOB-2009 noisy testbed. The (1+1)-CMA-ES is an adaptive stochastic algorithm for the optimization of objective functions d...
Anne Auger, Nikolaus Hansen
INFORMATICALT
2000
108views more  INFORMATICALT 2000»
15 years 6 months ago
Theoretical Foundations of an Environment-Based Multiparadigm Language
The paper presents a simple programming language and rewriting system called GENS. It is based on an extension of the -calculus called E-calculus. GENS is a multiparadigm language:...
Mario Blazevic, Zoran Budimac, Mirjana Ivanovic
GECCO
2009
Springer
113views Optimization» more  GECCO 2009»
15 years 11 months ago
Variable size population for dynamic optimization with genetic programming
A new model of Genetic Programming with variable size population is presented in this paper and applied to the reconstruction of target functions in dynamic environments (i.e. pro...
Leonardo Vanneschi, Giuseppe Cuccu