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Bayesian learning versus optimal learning

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  • Gordon, Mirta B
  • Buhot, Arnaud

Abstract

We consider the optimal performance that may be reached in the problem of learning the symmetry-breaking direction of a cloud of P=αN points in a N-dimensional space. The performance is measured through the overlap Ropt between the true symmetry-breaking direction and the learnt one. Depending on the problem, the learning curves Ropt(α) may present discontinuities. We show that close to these, bayesian learning is not optimal.

Suggested Citation

  • Gordon, Mirta B & Buhot, Arnaud, 1998. "Bayesian learning versus optimal learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 257(1), pages 85-98.
    • Handle: RePEc:eee:phsmap:v:257:y:1998:i:1:p:85-98
    DOI: 10.1016/S0378-4371(98)00130-7
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