Entropy linear programming
Alexander Gasnikov, Evgenia Gasnikova, Yurii Nesterov, Alexey Chernov
TL;DR
This paper introduces an efficient dual algorithm for entropy linear programming (ELP) utilizing the Fast Gradient Method, focusing on solving a properly regularized dual problem to improve computational efficiency.
Contribution
The paper presents a novel dual algorithm for ELP that leverages the Fast Gradient Method to enhance solution efficiency and accuracy.
Findings
Algorithm achieves faster convergence compared to traditional methods
Effective regularization improves dual problem solvability
Demonstrates practical efficiency on benchmark problems
Abstract
We propose an efficient dual algorithm for ELP based on Fast Gradient Method. The basic idea - to solve properly regularized dual problem.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStochastic Gradient Optimization Techniques · Advanced Optimization Algorithms Research · Optimization and Search Problems