lchizat/2019-sparse-optim-measures
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This is the julia code for the paper Sparse Optimization on Measures with Over-parameterized Gradient Descent Lenaic Chizat, 2019. In order to reproduce the experiments, you need to install julia 1.0 (or later) and the following packages: PyPlot, ProgressMeter, Random, LinearAlgebra. Then in julia prompt run include("filename.jl") The running times for a standard laptop are: illustration_generic (10 seconds) illustration_reluNN (4 seconds) illustration_deconv1D (5 seconds) illustration_deconv2D (5 minutes) cvgce_deconv2D (13 minutes) cvgce_2NNalt (30 minutes) success_deconv1D (2 minutes) success_2NNalt (40 minutes) vertical_compare (13 minutes)
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Source code for the paper "Sparse Optimization on Measures with Over-parameterized Gradient Descent"
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