University of Birmingham > Talks@bham > Artificial Intelligence and Natural Computation seminars > Inferring the appropriate architecture of a student network learning from a hard teacher

Inferring the appropriate architecture of a student network learning from a hard teacher

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If you have a question about this talk, please contact Per Kristian Lehre.

We investigated the problem of finding the appropriate architecture of a feed-forward network learning from a generic Boolean teacher. We found that the complexity measure defined through the averaged discrepancy, appears to provide a reasonable answer to this problem. In particular we found that for balanced functions with continuous average discrepancy the student network can be represented by a layered committee whit a hierarchical structure of synaptic vectors.

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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