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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

Pursuit of the Cluster Structure of Network Lasso: Recovery Condition and Non-convex Extension JMLR 2024
Sample-and-Bound for Non-convex Optimization AAAI 2024
Hierarchical Federated Learning with Multi-Timescale Gradient Correction NIPS 2024
Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion NIPS 2024
Adaptive Variance Reduction for Stochastic Optimization under Weaker Assumptions NIPS 2024
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates ALT 2024
Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions NIPS 2024
Decentralized Learning: Theoretical Optimality and Practical Improvements JMLR 2023
Escaping saddle points in zeroth-order optimization: the power of two-point estimators ICML 2023
Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval JMLR 2023
High Probability Convergence of Stochastic Gradient Methods ICML 2023
A Unified Framework for Optimization-Based Graph Coarsening JMLR 2023
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions ICML 2023
Approximate Inference in Logical Credal Networks IJCAI 2023
Towards Sustainable Learning: Coresets for Data-efficient Deep Learning ICML 2023
Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function ICML 2023
Analysis of Error Feedback in Federated Non-Convex Optimization with Biased Compression: Fast Convergence and Partial Participation ICML 2023
Special Properties of Gradient Descent with Large Learning Rates ICML 2023
Beyond Lipschitz Smoothness: A Tighter Analysis for Nonconvex Optimization ICML 2023
Coordinate Descent Methods for Fractional Minimization ICML 2023
A Line-Search Descent Algorithm for Strict Saddle Functions with Complexity Guarantees JMLR 2023
Accelerated Stochastic Optimization Methods under Quasar-convexity ICML 2023
Optimization for Amortized Inverse Problems ICML 2023
GradMA: A Gradient-Memory-Based Accelerated Federated Learning With Alleviated Catastrophic Forgetting CVPR 2023
Linear Regularizers Enforce the Strict Saddle Property AAAI 2023