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» Learning the required number of agents for complex tasks
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JALC
2007
90views more  JALC 2007»
13 years 7 months ago
Learning Unary Automata
We determine the complexity of learning problems for unary regular languages. We begin by investigating the minimum consistent dfa (resp. nfa) problem which is known not to be app...
Gregor Gramlich, Ralf Herrmann
ICML
2010
IEEE
13 years 8 months ago
Restricted Boltzmann Machines are Hard to Approximately Evaluate or Simulate
Restricted Boltzmann Machines (RBMs) are a type of probability model over the Boolean cube {-1, 1}n that have recently received much attention. We establish the intractability of ...
Philip M. Long, Rocco A. Servedio
ISRR
2005
Springer
149views Robotics» more  ISRR 2005»
14 years 1 months ago
Emergence, Exploration and Learning of Embodied Behavior
A novel model for dynamic emergence and adaptation of embodied behavior is proposed. A musculo-skeletal system is controlled by a number of chaotic elements, each of which driving...
Yasuo Kuniyoshi, Shinsuke Suzuki, Shinji Sangawa
NIPS
1989
13 years 9 months ago
The Cascade-Correlation Learning Architecture
Cascade-Correlation is a new architecture and supervised learning algorithm for artificial neural networks. Instead of just adjusting the weights in a network of fixed topology,...
Scott E. Fahlman, Christian Lebiere
PRL
2007
138views more  PRL 2007»
13 years 7 months ago
Ent-Boost: Boosting using entropy measures for robust object detection
Recently, boosting has come to be used widely in object-detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifier...
Duy-Dinh Le, Shin'ichi Satoh