The committee machine: Computational to statistical gaps in learning a two-layers neural network

NeurIPS 2018 Benjamin AubinAntoine MaillardJean BarbierFlorent KrzakalaNicolas MacrisLenka Zdeborová

Heuristic tools from statistical physics have been used in the past to locate the phase transitions and compute the optimal learning and generalization errors in the teacher-student scenario in multi-layer neural networks. In this contribution, we provide a rigorous justification of these approaches for a two-layers neural network model called the committee machine... (read more)

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