Convex-Concave Backtracking for Inertial Bregman Proximal Gradient
Algorithms in Non-Convex Optimization

v1v2 (latest)

Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Non-Convex Optimization

6 April 2019

Mahesh Chandra Mukkamala

ArXiv (abs)PDF HTML

Papers citing "Convex-Concave Backtracking for Inertial Bregman Proximal Gradient Algorithms in Non-Convex Optimization"

7 / 7 papers shown

Title
Diffusion at Absolute Zero: Langevin Sampling Using Successive Moreau Envelopes [conference paper] Andreas Habring Alexander Falk Thomas Pock 106 0 0 03 Feb 2025
Lifted Bregman Training of Neural Networks Xiaoyu Wang Martin Benning 39 6 0 18 Aug 2022
A Refined Inertial DC Algorithm for DC Programming Yu You Yi-Shuai Niu 19 7 0 30 Apr 2021
Global Convergence of Model Function Based Bregman Proximal Minimization Algorithms Mahesh Chandra Mukkamala M. Fadili Peter Ochs 71 8 0 24 Dec 2020
Inexact-ADMM Based Federated Meta-Learning for Fast and Continual Edge Learning Sheng Yue Ju Ren Jiang Xin Sen Lin Junshan Zhang FedML 70 44 0 16 Dec 2020
Bregman Proximal Framework for Deep Linear Neural Networks Mahesh Chandra Mukkamala Felix Westerkamp Emanuel Laude Daniel Cremers Peter Ochs 77 7 0 08 Oct 2019
Beyond Alternating Updates for Matrix Factorization with Inertial Bregman Proximal Gradient Algorithms Mahesh Chandra Mukkamala Peter Ochs 78 23 0 22 May 2019