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Mini-batch and distributed SAGA

MATLAB 19.98% Makefile 0.32% Python 6.51% Jupyter Notebook 27.76% TeX 45.42%

saga's Introduction

This small project explored two approaches to improve the SAGA incremental gradient algorithm:

  1. Take gradients over mini-batches to reduce the memory requirement.
  2. Compute gradients in parallel on multiple CPU cores to speed it up.

See our small report for an exposition of the methods and some experimental results.

You'll also find a Python implementation of our mini-batch approach as well as a MATLAB implementation of our distributed approach.

saga's People

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mdeff avatar sorooshafiee avatar

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