where f is a convex function. Solvable in polynomial time (interior point methods). Includes LP, QP with positive-definite Q, SDP. Non-Convex Optimization: same structure but f or constraints are ...

Abstract: This article presents a prediction-correction proximal method (PCPM) for the general nonsmooth convex optimization problem with linear equality and inequality constraints. The proposed ...

Abstract: This article aims to solve the distributed online convex optimization (DOCO) problems subjected to multiple coupled constraints over time-varying (TV) unbalanced digraphs. The existing ...

Data-driven decision-making processes increasingly utilize end-to-end learnable deep neural networks to render final decisions. Sometimes, the output of the forward functions in certain layers is ...

The goal of this course is to investigate in-depth and to develop expert knowledge in the theory and algorithms for convex optimization. This course will provide a rigorous introduction to the rich ...

This repository contains the projects and homework assignments for the Convex Optimization course, based on the book Convex Optimization by Stephen Boyd and associated lecture slides. The course ...

This course discusses basic convex analysis (convex sets, functions, and optimization problems), optimization theory (linear, quadratic, semidefinite, and geometric programming; optimality conditions ...