PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.

Code of the Performance Estimation Toolbox (PESTO) whose aim is to ease the access to the PEP methodology for performing worst-case analyses of first-order methods in convex and nonconvex optimization. The numerical worst-case analyses from PEP can be performed just by writting the algorithms just as you would implement them.

🎉 tada!: auTomAtic orDer of growth Analysis

This code can be used to reproduce all results from the paper "Smooth strongly convex interpolation and exact worst-case performance of first-order methods" (published in Mathematical Programming). (newer version available in the PESTO toolbox)

This code can be used to reproduce most results from the paper " Exact Worst-case Performance of First-order Methods for Composite Convex Optimization" (Published in SIAM Journal on Optimization). (newer version available in the PESTO toolbox!)

Introduction to Algorithm Design

Classical data structures: C++: vector, linked list, stack, queue, binary search tree, and graph representations. Worst-case analysis, amortized analysis, and big-O notation. Object-oriented and recursive implementation of data structures. Self-resizing vectors and self-balancing trees. Empirical performance measurement.

Time Complexity comparison of Insertion, Selection & Bubble sort using JFreeChart AWT output graph

Gebze Technical University Computer Engineering 2019-2020 homeworks

Prime Numbers, Probability, Start Talking, Develop Rules and Patterns, Worst Case Shifting, Algorithm Approaches

Copula Marginal Algorithm