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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
15 years 1 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
ICML
2006
IEEE
16 years 4 months ago
Experience-efficient learning in associative bandit problems
We formalize the associative bandit problem framework introduced by Kaelbling as a learning-theory problem. The learning environment is modeled as a k-armed bandit where arm payof...
Alexander L. Strehl, Chris Mesterharm, Michael L. ...
165
Voted
CVPR
2009
IEEE
16 years 11 months ago
Boosted Multi-Task Learning for Face Verification With Applications to Web Image and Video Search
Face verification has many potential applications including filtering and ranking image/video search results on celebrities. Since these images/videos are taken under uncontrolle...
Xiaogang Wang (MIT), Cha Zhang (Microsoft Research...
CVPR
2000
IEEE
16 years 5 months ago
Optimizing Learning in Image Retrieval
Combining learning with vision techniques in interactive image retrieval has been an active research topic during the past few years. However, existing learning techniques either ...
Yong Rui, Thomas S. Huang
117
Voted
ECAI
2004
Springer
15 years 9 months ago
Combining Multiple Answers for Learning Mathematical Structures from Visual Observation
Learning general truths from the observation of simple domains and, further, learning how to use this knowledge are essential capabilities for any intelligent agent to understand ...
Paulo Santos, Derek R. Magee, Anthony G. Cohn, Dav...