nonconvex optimization - Robuta Search

https://openreview.net/forum?id=IzqZbNMZ0M Private Zeroth-Order Nonsmooth Nonconvex Optimization | OpenReview We introduce a new zeroth-order algorithm for private stochastic optimization on nonconvex and nonsmooth objectives. Given a dataset of size $M$, our algorithm... zeroth order nonconvex optimization private openreview https://openreview.net/forum?id=B1eWhBrxIH&referrer=%5Bthe%20profile%20of%20Mehmet%20Fatih%20Sahin%5D(%2Fprofile%3Fid%3D~Mehmet_Fatih_Sahin2) An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints |... We propose a practical inexact augmented Lagrangian method (iALM) for nonconvex problems with nonlinear constraints. We characterize the total computational... nonconvex optimization inexact augmented lagrangian framework https://openreview.net/forum?id=iZgECfyHXF On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback | OpenReview Online nonconvex optimization has been an active area of research recently. Previous studies either considered the global regret with full information about... on the nonconvex optimization https://openreview.net/forum?id=VA1YpcNr7ul DASHA: Distributed Nonconvex Optimization with Communication Compression and Optimal Oracle... We provide a new method that improves the state-of-the-art theoretical complexity of distributed optimization methods with compressed communication in the... nonconvex optimization dasha distributed communication compression https://openreview.net/forum?id=hx2Ckkzdf53 Stochastic Anderson Mixing for Nonconvex Stochastic Optimization | OpenReview We propose a stochastic version of Anderson mixing which has theoretical guarantees and shows promising results in training neural networks. nonconvex optimization stochastic anderson mixing openreview https://deepai.org/publication/nonconvex-optimization-via-mm-algorithms-convergence-theory Nonconvex Optimization via MM Algorithms: Convergence Theory | DeepAI Jun 5, 2021 - 06/05/21 - The majorization-minimization (MM) principle is an extremely general framework for deriving optimization algorithms. It includes t... nonconvex optimization convergence theory via mm algorithms https://openreview.net/forum?id=ytke6qKpxtr STORM+: Fully Adaptive SGD with Recursive Momentum for Nonconvex Optimization | OpenReview In this work we investigate stochastic non-convex optimization problems where the objective is an expectation over smooth loss functions, and the goal is to... with recursive nonconvex optimization storm fully adaptive https://openreview.net/forum?id=EDVIHPZhFo Nonconvex-nonconcave min-max optimization on Riemannian manifolds | OpenReview This work studies nonconvex-nonconcave min-max problems on Riemannian manifolds. We first characterize the local optimality of nonconvex-nonconcave problems on... min max optimization riemannian manifolds nonconvex openreview https://arxiv.org/abs/1702.08627 [1702.08627] An Optimization Framework with Flexible Inexact Inner Iterations for Nonconvex and... Abstract page for arXiv paper 1702.08627: An Optimization Framework with Flexible Inexact Inner Iterations for Nonconvex and Nonsmooth Programming https://arxiv.org/abs/2404.09438?context=cs.LG [2404.09438] Developing Lagrangian-based Methods for Nonsmooth Nonconvex Optimization Abstract page for arXiv paper 2404.09438: Developing Lagrangian-based Methods for Nonsmooth Nonconvex Optimization 2404 developing lagrangian based methods https://openreview.net/forum?id=jj1o2SD3PB Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization | OpenReview Minimax optimization recently is widely applied in many machine learning tasks such as generative adversarial networks, robust learning and reinforcement... enhanced adaptive gradient algorithms nonconvex https://openreview.net/forum?id=AUeTkSymOq Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with... In practical distributed systems, workers are typically not homogeneous, and due to differences in hardware configurations and network conditions, can have... https://openreview.net/forum?id=mHyCz0KHOu&referrer=%5Bthe%20profile%20of%20Francesco%20Orabona%5D(%2Fprofile%3Fid%3D~Francesco_Orabona1) Dual Averaging Converges for Nonconvex Smooth Stochastic Optimization | OpenReview Dual averaging and gradient descent with their stochastic variants stand as the two canonical recipe books for first-order optimization: Every modern variant... stochastic optimization dual averaging converges nonconvex https://openreview.net/forum?id=AJwlILrBOr Nonconvex Meta-optimization for Deep Learning | OpenReview Hyperparameter tuning in mathematical optimization is a notoriously difficult problem. Recent tools from online control give rise to a provable methodology for... meta optimization deep learning nonconvex openreview https://arxiv.org/abs/1606.02338 [1606.02338] The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic... Abstract page for arXiv paper 1606.02338: The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALM the sound of https://arxiv.org/abs/2403.10547 [2403.10547] Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix... Abstract page for arXiv paper 2403.10547: Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing