Sep 12, 2022 · Second, we propose the gradient-free method (GFM) and stochastic GFM for solving a class of nonsmooth nonconvex optimization problems and prove ...

We propose and analyze a gradient-free method (GFM) and stochastic GFM for solving a class of nonsmooth nonconvex optimization problems. Both of these methods ...

Oct 31, 2022 · Second, we propose the gradient-free method (GFM) and stochastic GFM for solving a class of nonsmooth nonconvex optimization problems and prove ...

Sep 24, 2022 · PDF | Nonsmooth nonconvex optimization problems broadly emerge in machine learning and business decision making, whereas two core challenges ...

Oct 17, 2022 · In this paper, we propose and analyze a class of deterministic and stochastic gradient- free methods for nonsmooth nonconvex optimization ...

Apr 3, 2024 · Second, we propose the gradient-free method (GFM) and stochastic GFM for solving a class of nonsmooth nonconvex optimization problems and prove ...

PAGE: A simple and optimal probabilistic gradient estimator for nonconvex optimization. In ICML, 2021. Lin, T., Zheng, Z., and Jordan, M. I. Gradient-free ...

Sep 12, 2022 · Second, we propose the gradient-free method (GFM) and stochastic GFM for solving a class of nonsmooth nonconvex optimization problems and prove ...

A more efficient algorithm using stochastic recursive gradient estimators is proposed, which improves the complexity to the recently proposed gradient-free ...

In this work, we propose two gradient-free decentralized al- gorithms for non-smooth non-convex optimization: the De- centralized Gradient Free Method (DGFM) ...