Stochastic model-based minimization under high-order growth

1 July 2018

Papers citing "Stochastic model-based minimization under high-order growth"

13 / 13 papers shown

Title
Stochastic Weakly Convex Optimization Beyond Lipschitz Continuity Wenzhi Gao Qi Deng 61 1 0 25 Jan 2024
Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow Rentian Yao Linjun Huang Yun Yang 84 4 0 01 Nov 2023
Revisiting Subgradient Method: Complexity and Convergence Beyond Lipschitz Continuity Xiao Li Lei Zhao Daoli Zhu Anthony Man-Cho So 23 3 0 23 May 2023
Delayed Stochastic Algorithms for Distributed Weakly Convex Optimization W. Gao Qinhao Deng 76 0 0 30 Jan 2023
SPIRAL: A superlinearly convergent incremental proximal algorithm for nonconvex finite sum minimization Pourya Behmandpoor P. Latafat Andreas Themelis Marc Moonen Panagiotis Patrinos 59 2 0 17 Jul 2022
Efficient algorithms for implementing incremental proximal-point methods A. Shtoff 69 1 0 03 May 2022
Stochastic Mirror Descent for Low-Rank Tensor Decomposition Under Non-Euclidean Losses Wenqiang Pu Shahana Ibrahim Xiao Fu Mingyi Hong 126 9 0 29 Apr 2021
Global Convergence of Model Function Based Bregman Proximal Minimization Algorithms Mahesh Chandra Mukkamala M. Fadili Peter Ochs 75 8 0 24 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 87 23 0 22 May 2019
Model Function Based Conditional Gradient Method with Armijo-like Line Search Yura Malitsky Peter Ochs 47 4 0 23 Jan 2019
Graphical Convergence of Subgradients in Nonconvex Optimization and Learning Damek Davis Dmitriy Drusvyatskiy 81 26 0 17 Oct 2018
The duality structure gradient descent algorithm: analysis and applications to neural networks Thomas Flynn 37 3 0 01 Aug 2017