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BinaryCommitteeMachineRSGD.jl

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This package implements the Replicated Stochastic Gradient Descent algorithm for committee machines with binary weights described in the paper Unreasonable Effectiveness of Learning Neural Networks: From Accessible States and Robust Ensembles to Basic Algorithmic Schemes by Carlo Baldassi, Christian Borgs, Jennifer Chayes, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti and Riccardo Zecchina, Proc. Natl. Acad. Sci. U.S.A. 113: E7655-E7662 (2016), doi:10.1073/pnas.1608103113.

The code is written in Julia.

The package requires Julia 0.7 or later.

Installation

To install the module, use these commands from within Julia:

julia> using Pkg

julia> Pkg.clone("https://github.com/carlobaldassi/BinaryCommitteeMachineRSGD.jl")

Dependencies will be installed automatically.

Documentation

  • LATESTin-development version of the documentation.

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Replicated Stochastic Gradient Descent on Commitee machines with binary weights

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