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1999 International Conference on Information Intelligence and Systems (ICIIS'99)
Adaptive On-Line Learning of Probability Distributions from Field Theories
Rockville, Maryland
March 31-April 03
ISBN: 0-7695-0446-9
Toshiaki Aida, Tokyo Metropolitan College of Aeronautical Engineering
N. The algorithm is based on how we can detect the change of a source function in non-supervised learning scheme. This is an extension of an optimal on-line learning algorithm of probability distributions, which is derived from the field theoretical point of view. Since we learn not parameters of a model but probability functions themselves, the algorithm has the advantage that it requires no a priori knowledge of a model.
Index Terms:
adaptive learning, non-parametric method, non-supervised learning
Citation:
Toshiaki Aida, "Adaptive On-Line Learning of Probability Distributions from Field Theories," iciis, pp.66, 1999 International Conference on Information Intelligence and Systems (ICIIS'99), 1999
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