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non-convex optimization

546 papers

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Also known as

IRLS

Co-occurring keywords

stochastic gradient descent (1088) stochastic optimization (1060) gradient descent (1143) convergence rate (606) convergence analysis (394) variance reduction (520) nonconvex optimization (316) saddle point (95) matrix factorization (529) online learning (1770)

Papers

Multiplicative Noise and Heavy Tails in Stochastic Optimization ICML 2021
A Second look at Exponential and Cosine Step Sizes: Simplicity, Adaptivity, and Performance ICML 2021
General Low-rank Matrix Optimization: Geometric Analysis and Sharper Bounds NIPS 2021
STORM+: Fully Adaptive SGD with Recursive Momentum for Nonconvex Optimization NIPS 2021
A Faster Decentralized Algorithm for Nonconvex Minimax Problems NIPS 2021
On the Convergence of Step Decay Step-Size for Stochastic Optimization NIPS 2021
Learning-to-learn non-convex piecewise-Lipschitz functions NIPS 2021
Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond NIPS 2021
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings NIPS 2021
A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets AISTATS 2021
Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent NIPS 2021
Convergence rates and approximation results for SGD and its continuous-time counterpart COLT 2021
Escape saddle points by a simple gradient-descent based algorithm NIPS 2021
Stochastic Proximal Methods for Non-Smooth Non-Convex Constrained Sparse Optimization JMLR 2021
Landscape analysis of an improved power method for tensor decomposition NIPS 2021
An Online Method for A Class of Distributionally Robust Optimization with Non-convex Objectives NIPS 2021
Communication Efficient SGD via Gradient Sampling With Bayes Prior CVPR 2021
A Hybrid Variance-Reduced Method for Decentralized Stochastic Non-Convex Optimization ICML 2021
SGD with shuffling: optimal rates without component convexity and large epoch requirements NIPS 2020
Safe Sample Screening for Robust Support Vector Machine AAAI 2020
Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization NIPS 2020
A Stochastic Derivative-Free Optimization Method with Importance Sampling: Theory and Learning to Control AAAI 2020
Tight Convergence Rate of Gradient Descent for Eigenvalue Computation IJCAI 2020
A Simple and Efficient Smoothing Method for Faster Optimization and Local Exploration NIPS 2020
Optimal Learning from Verified Training Data NIPS 2020