Abstract: Many online problems, for example, online network resource allocation in the resource-constrained cloud environment, can be formulated as online convex optimization (OCO) problems with some ...

Abstract: Recently, deep unfolding networks (DUNs) have emerged as a promising technique for image Compressive Sensing (CS) reconstruction by unfolding optimization algorithms, where each stage of the ...

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 ...

where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...

This repository contains the slides on the convex-concave procedure from EE 364a, together with example code. To see the animations in the PDF file, you need to select a viewer that supports ...