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» Spectral Algorithms for Supervised Learning
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ESANN
2000
14 years 11 months ago
SpikeProp: backpropagation for networks of spiking neurons
Abstract. For a network of spiking neurons with reasonable postsynaptic potentials, we derive a supervised learning rule akin to traditional error-back-propagation, SpikeProp and s...
Sander M. Bohte, Joost N. Kok, Johannes A. La Pout...
IJCAI
1989
14 years 11 months ago
Noise-Tolerant Instance-Based Learning Algorithms
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...
David W. Aha, Dennis F. Kibler
CAI
2007
Springer
15 years 4 months ago
Learning Deterministically Recognizable Tree Series - Revisited
Abstract. We generalize a learning algorithm originally devised for deterministic all-accepting weighted tree automata (wta) to the setting of arbitrary deterministic wta. The lear...
Andreas Maletti
FLAIRS
1998
14 years 11 months ago
Interactively Training Pixel Classifiers
Manual generation of training examples for supervised learning is an expensive process. One way to reduce this cost is to produce training instances that are highly informative. T...
Justus H. Piater, Edward M. Riseman, Paul E. Utgof...
ICMCS
2000
IEEE
142views Multimedia» more  ICMCS 2000»
15 years 2 months ago
Incorporate Discriminant Analysis with EM Algorithm in Image Retrieval
One of the difficulties of Content-Based Image Retrieval (CBIR) is the gap between high-level concepts and low-level image features, e.g., color and texture. Relevance feedback wa...
Qi Tian, Ying Wu, Thomas S. Huang