README.md

Acceleration Monograph

This code can be used to verify the theoretical statements from the monograph

[1] Alexandre d’Aspremont, Damien Scieur and Adrien Taylor (2021), "Acceleration Methods", Foundations and Trends® in Optimization: Vol. 5: No. 1-2, pp 1-245.

The arXiv version is available here, the Foundation and Trends version is available here.

Authors

• Alexandre d'Aspremont
• Damien Scieur
• Adrien Taylor

Notes:

• Files in the folders Proofs of Chapter 4/01_Symbolic and Proofs of Chapter 5/01_Symbolic require Mathematica (for verifying analytical developments).
• Files in the folders Proofs of Chapter 4/02_Numerical and Proofs of Chapter 5/02_Numerical require YALMIP along with a suitable SDP solver (e.g., Sedumi, SDPT3, Mosek), and the Performance Estimation Toolbox (PESTO).
• Files in the folders Proofs of Appendix C/ require Mathematica (for verifying analytical developments and performing the numerical experiments).

Content

(Accelerated) Gradient Methods (Chapter 4)

Proofs of Chapter 4 contains two subfolders.

• 01_Symbolic contains Mathematica notebooks for verifying the algebraic manipulations required in the proof of the potential inequalities for the 14 gradient methods in this chapter.
• 02_Numerical contains Matlab codes for verifying the final bounds of the methods presented in the chapter.

(Accelerated) Proximal Methods (Chapter 5)

Proofs of Chapter 5 contains two subfolders.

• 01_Symbolic contains Mathematica notebooks for verifying the algebraic manipulations required in the proof of the potential inequalities for the 4 proximal methods in this chapter.
• 02_Numerical contains Matlab codes for verifying the final bounds of the 4 proximal methods presented in the chapter.

On Worst-case Analyses for First-order Methods (Appendix C)

Proofs of Appendix C/ contains Mathematica notebooks for obtaining (analytically) and solving (numerically) the LMI formulations from Appendix C.