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FOCS
2008
IEEE
16 years 1 months ago
The Bayesian Learner is Optimal for Noisy Binary Search (and Pretty Good for Quantum as Well)
We use a Bayesian approach to optimally solve problems in noisy binary search. We deal with two variants: • Each comparison is erroneous with independent probability 1 − p. â€...
Michael Ben-Or, Avinatan Hassidim
ECML
2007
Springer
16 years 1 months ago
Fast Optimization Methods for L1 Regularization: A Comparative Study and Two New Approaches
L1 regularization is effective for feature selection, but the resulting optimization is challenging due to the non-differentiability of the 1-norm. In this paper we compare state...
Mark Schmidt, Glenn Fung, Rómer Rosales
GECCO
2007
Springer
191views Optimization» more  GECCO 2007»
16 years 1 months ago
An artificial immune system with partially specified antibodies
Artificial Immune System algorithms use antibodies which fully specify the solution of an optimization, learning, or pattern recognition problem. By being restricted to fully spec...
Ramin Halavati, Saeed Bagheri Shouraki, Mojdeh Jal...
GECCO
2007
Springer
532views Optimization» more  GECCO 2007»
16 years 1 months ago
Evolving evolutionary algorithms using evolutionary algorithms
A new model for automatic generation of Evolutionary Algorithms (EAs) by evolutionary means is proposed in this paper. The model is based on a simple Genetic Algorithm (GA). Every...
Laura Diosan, Mihai Oltean
GECCO
2005
Springer
16 years 12 days ago
Evolving agent swarms for clustering and sorting
Social insect societies consist of individuals with simple behavior, yet at the collective level the societies are capable of solving complex tasks. These tasks span a wide range,...
Vegard Hartmann