Convex Optimization and Mathematical Imaging

I'm now constructing the course of Convex Optimization with Applications to Image Processing, Computer Vision and Machine Learning. 

Main Contents

• • First touch to convex optimization: what's convex optimization, why and how convex optimization is important

  • Another expressions: duality theory - ask the dual if you have troubles

  • Variational analysis: how to mathematically analyze a practical problem, what's the beauty of variations

  • Fast numerical solvers (I): how and why convex optimization leads to fast and reliable algorithms, how to achieve a better convergence rate in numerics

  • Fast numerical solvers (II): how and why multiplier theories help to improve numerical algorithms

  • Convex optimization to non-convex and integer optimization problems: what a challenge comes from practical problems, how can convex relaxation helps

  • Special practical topics: how to apply math in real problems, e.g. image denoising and restoration, image segmentation and labeling, machine learning 

Textbooks

• • Convex Analysis and Optimization by Bertsekas

  • Nonlinear Programming by Bertsekas

  • Convex Optimization by Boyd and Vandenberghe

  • Lectures on modern convex optimization: analysis, algorithms, Engineering Applications by Ben-Tal and Nemirovskiĭ

Hopefully it works out and appears soon!