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AAAI
2006
13 years 9 months ago
Efficient L1 Regularized Logistic Regression
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
GECCO
2005
Springer
140views Optimization» more  GECCO 2005»
14 years 1 months ago
CGP visits the Santa Fe trail: effects of heuristics on GP
GP uses trees to represent chromosomes. The user defines the representation space by defining the set of functions and terminals to label the nodes in the trees, and GP searches t...
Cezary Z. Janikow, Christopher J. Mann
CODES
2003
IEEE
14 years 1 months ago
Design optimization of mixed time/event-triggered distributed embedded systems
Distributed embedded systems implemented with mixed, eventtriggered and time-triggered task sets, which communicate over bus protocols consisting of both static and dynamic phases...
Traian Pop, Petru Eles, Zebo Peng
WCE
2007
13 years 9 months ago
Local Approximation of Pareto Surface
—In the design process of complex systems, the designer is solving an optimization problem, which involves different disciplines and where all design criteria have to be optimize...
S. V. Utyuzhnikov, Jeremy Maginot, Marin D. Guenov
GECCO
2010
Springer
174views Optimization» more  GECCO 2010»
13 years 11 months ago
Real-coded genetic algorithm benchmarked on noiseless black-box optimization testbed
Genetic algorithms—a class of stochastic population-based optimization techniques—have been widely realized as the effective tools to solve complicated optimization problems ...
Thanh-Do Tran, Gang-Gyoo Jin