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

A Scalable and Exact Relaxation for Densest k-Subgraph via Error Bounds AAAI 2026

Super Level Sets and Exponential Decay: A Synergistic Approach to Stable Neural Network Training (Abstract Reprint) AAAI 2026

Hybrid Decentralized Optimization: Leveraging Both First- and Zeroth-Order Optimizers for Faster Convergence AAAI 2025

Last-iterate Convergence of Shuffling Momentum Gradient Method under the Kurdyka-Lojasiewicz Inequality JMLR 2025

Dyn-D^2P: Dynamic Differentially Private Decentralized Learning with Provable Utility Guarantee IJCAI 2025

Sharp Bounds for Sequential Federated Learning on Heterogeneous Data JMLR 2025

Non-Convex Tensor Recovery from Local Measurements AAAI 2025

Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent AAAI 2025

Improved Rates of Differentially Private Nonconvex-Strongly-Concave Minimax Optimization AAAI 2025

Convergence Analysis of Federated Learning Methods Using Backward Error Analysis AAAI 2025

Differentiable GPU-Parallelized Task and Motion Planning RSS 2025

Sample-Efficient Geometry Reconstruction from Euclidean Distances using Non-Convex Optimization NIPS 2024

Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions NIPS 2024

Stochastic Regularized Majorization-Minimization with weakly convex and multi-convex surrogates JMLR 2024

Ordered Momentum for Asynchronous SGD NIPS 2024

AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms AISTATS 2024

Fast and Accurate Estimation of Low-Rank Matrices from Noisy Measurements via Preconditioned Non-Convex Gradient Descent AISTATS 2024

Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases AISTATS 2024

Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss NIPS 2024

Federated Learning under Periodic Client Participation and Heterogeneous Data: A New Communication-Efficient Algorithm and Analysis NIPS 2024

On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions NIPS 2024

Non-geodesically-convex optimization in the Wasserstein space NIPS 2024

Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization Approach AISTATS 2024

Globally Q-linear Gauss-Newton Method for Overparameterized Non-convex Matrix Sensing NIPS 2024

Pursuit of the Cluster Structure of Network Lasso: Recovery Condition and Non-convex Extension JMLR 2024