Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization

17 February 2020

Papers citing "Stochastic Gauss-Newton Algorithms for Nonconvex Compositional Optimization"

12 / 12 papers shown

Title
Solving Nonlinear PDEs with Sparse Radial Basis Function Networks Zihan Shao Konstantin Pieper Xiaochuan Tian 29 0 0 12 May 2025
Incremental Gauss-Newton Descent for Machine Learning Mikalai Korbit Mario Zanon ODL 17 0 0 10 Aug 2024
Exact Gauss-Newton Optimization for Training Deep Neural Networks Mikalai Korbit Adeyemi Damilare Adeoye Alberto Bemporad Mario Zanon ODL 28 0 0 23 May 2024
Dual Gauss-Newton Directions for Deep Learning Vincent Roulet Mathieu Blondel ODL 16 0 0 17 Aug 2023
Modified Gauss-Newton Algorithms under Noise Krishna Pillutla Vincent Roulet Sham Kakade Zaïd Harchaoui 16 3 0 18 May 2023
Linearization Algorithms for Fully Composite Optimization Maria-Luiza Vladarean N. Doikov Martin Jaggi Nicolas Flammarion 15 3 0 24 Feb 2023
Efficient algorithms for implementing incremental proximal-point methods A. Shtoff 9 1 0 03 May 2022
Finite-Sum Optimization: A New Perspective for Convergence to a Global Solution Lam M. Nguyen Trang H. Tran Marten van Dijk 28 3 0 07 Feb 2022
Tighter Analysis of Alternating Stochastic Gradient Method for Stochastic Nested Problems Tianyi Chen Yuejiao Sun W. Yin 24 33 0 25 Jun 2021
A Single-Timescale Method for Stochastic Bilevel Optimization Tianyi Chen Yuejiao Sun Quan-Wu Xiao W. Yin 16 76 0 09 Feb 2021
Progressive Batching for Efficient Non-linear Least Squares Huu Le Christopher Zach E. Rosten Oliver J. Woodford 6 3 0 21 Oct 2020
Hybrid Variance-Reduced SGD Algorithms For Nonconvex-Concave Minimax Problems Quoc Tran-Dinh Deyi Liu Lam M. Nguyen 22 13 0 27 Jun 2020