Statistical Mechanics of Learning: A Variational Approach for Real Data
arXiv:cond-mat/0209164 · doi:10.1103/PhysRevLett.89.108302
Abstract
Using a variational technique, we generalize the statistical physics approach of learning from random examples to make it applicable to real data. We demonstrate the validity and relevance of our method by computing approximate estimators for generalization errors that are based on training data alone.
4 pages, 2 figures
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