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165
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NIPS
1992
15 years 4 months ago
A Note on Learning Vector Quantization
Vector Quantization is useful for data compression. Competitive Learning which minimizes reconstruction error is an appropriate algorithm for vector quantization of unlabelled dat...
Virginia R. de Sa, Dana H. Ballard
132
Voted
KDD
2007
ACM
149views Data Mining» more  KDD 2007»
16 years 4 months ago
Distributed classification in peer-to-peer networks
This work studies the problem of distributed classification in peer-to-peer (P2P) networks. While there has been a significant amount of work in distributed classification, most o...
Ping Luo, Hui Xiong, Kevin Lü, Zhongzhi Shi
115
Voted
MVA
1990
15 years 4 months ago
A Pattern Classifier Integrating Multilayer Perceptron and Error-Correcting Code
In this paper we present a novel classifier which integrates a multilayer perceptron and a error-correcting decoder. There are two stages in the classifier,in the first stage, map...
Haibo Li, Torbjörn Kronander, Ingemar Ingemar...
164
Voted
BMCBI
2005
131views more  BMCBI 2005»
15 years 3 months ago
Regularized Least Squares Cancer Classifiers from DNA microarray data
Background: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information ...
Nicola Ancona, Rosalia Maglietta, Annarita D'Addab...
102
Voted
NIPS
2001
15 years 5 months ago
Playing is believing: The role of beliefs in multi-agent learning
We propose a new classification for multi-agent learning algorithms, with each league of players characterized by both their possible strategies and possible beliefs. Using this c...
Yu-Han Chang, Leslie Pack Kaelbling