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ALT
2008
Springer
15 years 8 months ago
Optimal Language Learning
Gold’s original paper on inductive inference introduced a notion of an optimal learner. Intuitively, a learner identifies a class of objects optimally iff there is no other lea...
John Case, Samuel E. Moelius
NN
1998
Springer
108views Neural Networks» more  NN 1998»
14 years 11 months ago
How embedded memory in recurrent neural network architectures helps learning long-term temporal dependencies
Learning long-term temporal dependencies with recurrent neural networks can be a difficult problem. It has recently been shown that a class of recurrent neural networks called NA...
Tsungnan Lin, Bill G. Horne, C. Lee Giles
IROS
2006
IEEE
107views Robotics» more  IROS 2006»
15 years 5 months ago
Learning Sensory-Motor Maps for Redundant Robots
— Humanoid robots are routinely engaged in tasks requiring the coordination between multiple degrees of freedom and sensory inputs, often achieved through the use of sensorymotor...
Manuel Lopes, José Santos-Victor
77
Voted
CIMCA
2005
IEEE
15 years 5 months ago
An Accelerating Learning Algorithm for Block-Diagonal Recurrent Neural Networks
An efficient training method for block-diagonal recurrent neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static models, in order to...
Paris A. Mastorocostas, Dimitris N. Varsamis, Cons...
ICONIP
2004
15 years 25 days ago
Neural-Evolutionary Learning in a Bounded Rationality Scenario
Abstract. This paper presents a neural-evolutionary framework for the simulation of market models in a bounded rationality scenario. Each agent involved in the scenario make use of...
Ricardo Matsumura de Araújo, Luís C....