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AAAI
2011
14 years 6 months ago
Heterogeneous Transfer Learning with RBMs
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Bin Wei, Christopher Pal
DATE
2007
IEEE
167views Hardware» more  DATE 2007»
16 years 1 months ago
A decomposition-based constraint optimization approach for statically scheduling task graphs with communication delays to multip
We present a decomposition strategy to speed up constraint optimization for a representative multiprocessor scheduling problem. In the manner of Benders decomposition, our techniq...
Nadathur Satish, Kaushik Ravindran, Kurt Keutzer
BC
1998
109views more  BC 1998»
15 years 6 months ago
Learning and stabilization of altruistic behaviors in multi-agent systems by reciprocity
Optimization of performance in collective systems often requires altruism. The emergence and stabilization of altruistic behaviors are dicult to achieve because the agents incur ...
Javier Zamora, José del R. Millán, A...
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
15 years 4 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
ATAL
2006
Springer
15 years 10 months ago
Learning against multiple opponents
We address the problem of learning in repeated N-player (as opposed to 2-player) general-sum games. We describe an extension to existing criteria focusing explicitly on such setti...
Thuc Vu, Rob Powers, Yoav Shoham