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» Extracting Propositions from Trained Neural Networks
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NIPS
1992
14 years 10 months ago
Explanation-Based Neural Network Learning for Robot Control
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
Tom M. Mitchell, Sebastian Thrun
NN
2007
Springer
14 years 9 months ago
From memory-based decisions to decision-based movements: A model of interval discrimination followed by action selection
The interval discrimination task is a classical experimental paradigm that is employed to study working memory and decision making and typically involves four phases. First, the s...
Prashant Joshi
ICRA
1998
IEEE
105views Robotics» more  ICRA 1998»
15 years 1 months ago
PSOM Network: Learning with Few Examples
: Precise sensorimotor mappings between various motor, ensor, and abstract physical spaces are the basis for many robotics tasks. Their cheap construction is a challenge for adapti...
Jörg A. Walter
84
Voted
LREC
2008
134views Education» more  LREC 2008»
14 years 11 months ago
Evaluation of Lexical Resources and Semantic Networks on a Corpus of Mental Associations
When a user cannot find a word, he may think of semantically related words that could be used into an automatic process to help him. This paper presents an evaluation of lexical r...
Laurianne Sitbon, Patrice Bellot, Philippe Blache
SPEECH
2002
113views more  SPEECH 2002»
14 years 9 months ago
Estimation of the signal-to-noise ratio with amplitude modulation spectrograms
An algorithm is proposed which automatically estimates the local signalto-noise ratio (SNR) between speech and noise. The feature extraction stage of the algorithm is motivated by...
Jürgen Tchorz, Birger Kollmeier