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NIPS
2007
15 years 8 months ago
The Tradeoffs of Large Scale Learning
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Léon Bottou, Olivier Bousquet
UIST
2006
ACM
16 years 17 days ago
Viz: a visual analysis suite for explaining local search behavior
NP-hard combinatorial optimization problems are common in real life. Due to their intractability, local search algorithms are often used to solve such problems. Since these algori...
Steven Halim, Roland H. C. Yap, Hoong Chuin Lau
GECCO
2007
Springer
174views Optimization» more  GECCO 2007»
16 years 23 days ago
Heuristic speciation for evolving neural network ensemble
Speciation is an important concept in evolutionary computation. It refers to an enhancements of evolutionary algorithms to generate a set of diverse solutions. The concept is stud...
Shin Ando
DAC
2010
ACM
15 years 10 months ago
Eyecharts: constructive benchmarking of gate sizing heuristics
—Discrete gate sizing is one of the most commonly used, flexible, and powerful techniques for digital circuit optimization. The underlying problem has been proven to be NP-hard ...
Puneet Gupta, Andrew B. Kahng, Amarnath Kasibhatla...
GECCO
2008
Springer
172views Optimization» more  GECCO 2008»
15 years 7 months ago
Empirical analysis of a genetic algorithm-based stress test technique
Evolutionary testing denotes the use of evolutionary algorithms, e.g., Genetic Algorithms (GAs), to support various test automation tasks. Since evolutionary algorithms are heuris...
Vahid Garousi