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

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

A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs NIPS 2024

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

Almost Sure Convergence Rates Analysis and Saddle Avoidance of Stochastic Gradient Methods JMLR 2024

Bridging the Gap between General and Down-Closed Convex Sets in Submodular Maximization IJCAI 2024

Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation NIPS 2024

SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization AISTATS 2024

Absence of spurious solutions far from ground truth: A low-rank analysis with high-order losses AISTATS 2024

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

A large deviations perspective on policy gradient algorithms L4DC 2024

High Probability Convergence Bounds for Non-convex Stochastic Gradient Descent with Sub-Weibull Noise JMLR 2024

Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes NIPS 2024

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

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

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

Stochastic Optimization Schemes for Performative Prediction with Nonconvex Loss NIPS 2024

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

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

Generalization Bounds for Label Noise Stochastic Gradient Descent AISTATS 2024

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

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

No Internal Regret with Non-convex Loss Functions AAAI 2024

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

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

Hierarchical Federated Learning with Multi-Timescale Gradient Correction NIPS 2024