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Competitive learning

Competitive learning is a form of unsupervised learning in artificial neural networks, in which nodes compete for the right to respond to a subset of… 
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Related topics

Related topics

11 relations
Artificial intelligenceCluster analysisEncog Machine Learning FrameworkEnsemble learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2008
2008
Relational-Cultural Practice: Working in a Nonrelational World
SUMMARY While more and more clinicians are practicing a relational-cultural approach to therapy, many work in settings that… 
Highly Cited
2007
Highly Cited
2007
A unified perspective and new results on RHT computing, mixture based learning, and multi-learner based problem solving
2006
2006
A new feature extractor invariant to intensity, rotation, and scaling of color images
2006
2006
Nonlinear Projection Using Geodesic Distances and the Neural Gas Network
A nonlinear projection method that uses geodesic distances and the neural gas network is proposed. First, the neural gas… 
2004
2004
From mind in the mouth to language in the mind Language in Mind edited by D. Gentner and S. Goldin-Meadow, MIT Press, 2003. £22.95 (522 pages) ISBN 0 262 57163 3
2002
2002
A Simultaneous Descending Bid Auction for Multiple Items and Unitary Demand
This paper proposes a new descending bid method for auctioning multiple objects. The auctioneer announces a current price… 
Highly Cited
2001
Highly Cited
2001
Stochastic Neural Computation II: Soft Competitive Learning
For pt. I see ibid., p.891-905. An investigation has been made into the use of stochastic arithmetic to implement an artificial… 
1996
1996
Adaptive resonance theory based neural network for supervised chemical pattern recognition (FuzzyARTMAP) Part 2: Classification of post-consumer plastics by remote NIR spectroscopy using an InGaAs…
1996
1996
A network model for the optic flow computation of the MST neurons
1996
1996
Adaptive resonance theory based neural network for supervised chemical pattern recognition (FuzzyARTMAP) Part 1: Theory and network properties
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