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AdaSVRG

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Install / Use

/learn @bpauld/AdaSVRG
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

SVRG meets AdaGrad: Painless Variance Reduction

Experiments

Run the experiments using the command below:

python trainval.py -e $exp_{BENCHMARK} -sb ${SAVEDIR_BASE} -r 1

with the placeholders defined as follows. Use the notebook plot-experiments.ipynb to reproduce the plots.

{BENCHMARK}

Defines the dataset and regularization constant for the experiments

  • a1a, a2a, w8a, mushrooms, ijcnn, phishing, rcv1 for the experiments comparing AdaSVRG to classical methods (including SVRG).

  • synthetic_interpolation for the interpolation experiments.

  • a1a_diagonal, w8a_diagonal, mushrooms_diagonal for the experiments comparing the scalar and diagonal variants of AdaSVRG.

{SAVEDIR_BASE}

Defines the absolute path to where the results will be saved.

View on GitHub
GitHub Stars5
CategoryDevelopment
Updated1y ago
Forks2

Languages

Jupyter Notebook

Security Score

50/100

Audited on Dec 12, 2024

No findings