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A set of notebooks related to convex optimization, variational inference and numerical methods for signal processing, machine learning, deep learning, graph analysis, bayesian programming, statistics or astronomy.

gnthibault/Optimisation-Python

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Optimisation-Python

This repository is intends to gather some basic optimisation algorithms in python, in order to study their behaviour and compare them in the a generic framework. It may also contains some application designed to solve problems arising in the field of Machine Learning or Compressed Sensing.

Some of the ipython notebook you can find there have been originally designed by -Gabriel Peyré : http://www.numerical-tours.com/ And the version that has been used here has been modified by -Laurent Condat : http://www.gipsa-lab.grenoble-inp.fr/~laurent.condat/ Which are well reknown researcher in advanced optimisation technics for signal processing.

You may also be interested in some slides designed in the framework of a reading group at Eth-Zurich, were we studied the Convex Optimization book by Boyd and Vandenberg:

Chapter 1

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A set of notebooks related to convex optimization, variational inference and numerical methods for signal processing, machine learning, deep learning, graph analysis, bayesian programming, statistics or astronomy.

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