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ISSN
0899-7667
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1530-888X
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2.21

Neural Computation

November 1995, Vol. 7, No. 6, Pages 1206-1224
(doi: 10.1162/neco.1995.7.6.1206)
© 1995 Massachusetts Institute of Technology
Learning and Generalization with Minimerror, A Temperature-Dependent Learning Algorithm
Article PDF (811.31 KB)
Abstract

We study the numerical performances of Minimerror, a recently introduced learning algorithm for the perceptron that has analytically been shown to be optimal both on learning linearly and nonlinearly separable functions. We present its implementation on learning linearly separable boolean functions. Numerical results are in excellent agreement with the theoretical predictions.