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» Theoretical Analysis of Mission-Based Learning Model
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IJON
1998
158views more  IJON 1998»
14 years 11 months ago
Bayesian Kullback Ying-Yang dependence reduction theory
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...
Lei Xu
JMLR
2012
13 years 2 months ago
Sparse Additive Machine
We develop a high dimensional nonparametric classification method named sparse additive machine (SAM), which can be viewed as a functional version of support vector machine (SVM)...
Tuo Zhao, Han Liu
GECCO
2009
Springer
15 years 6 months ago
On the scalability of XCS(F)
Many successful applications have proven the potential of Learning Classifier Systems and the XCS classifier system in particular in datamining, reinforcement learning, and func...
Patrick O. Stalph, Martin V. Butz, David E. Goldbe...
NECO
2008
101views more  NECO 2008»
14 years 11 months ago
On the Classification Capability of Sign-Constrained Perceptrons
The perceptron (also referred to as McCulloch-Pitts neuron, or linear threshold gate) is commonly used as a simplified model for the discrimination and learning capability of a bi...
Robert A. Legenstein, Wolfgang Maass
EMMCVPR
1999
Springer
15 years 4 months ago
Markov Random Field Modelling of fMRI Data Using a Mean Field EM-algorithm
This paper considers the use of the EM-algorithm, combined with mean field theory, for parameter estimation in Markov random field models from unlabelled data. Special attention ...
Markus Svensén, Frithjof Kruggel, D. Yves v...