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COLT
2008
Springer
13 years 6 months ago
The Learning Power of Evolution
Vitaly Feldman, Leslie G. Valiant
CEC
2003
IEEE
13 years 10 months ago
Learning DFA: evolution versus evidence driven state merging
Learning Deterministic Finite Automata (DFA) is a hard task that has been much studied within machine learning and evolutionary computation research. This paper presents a new met...
Simon M. Lucas, T. Jeff Reynolds
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 2 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
ICPR
2008
IEEE
14 years 6 months ago
Incremental machine learning techniques for document layout understanding
In real-world Digital Libraries, Artificial Intelligence techniques are essential for tackling the automatic document processing task with sufficient flexibility. The great variab...
Floriana Esposito, Marenglen Biba, Stefano Ferilli...
JMLR
2008
141views more  JMLR 2008»
13 years 4 months ago
Accelerated Neural Evolution through Cooperatively Coevolved Synapses
Many complex control problems require sophisticated solutions that are not amenable to traditional controller design. Not only is it difficult to model real world systems, but oft...
Faustino J. Gomez, Jürgen Schmidhuber, Risto ...