non-convex

A Generalization Result for Convergence in Learning-to-Optimize ICML 2025 Compelling ReLU Networks to Exhibit Exponentially Many Linear Regions at Initialization and During Training ICML 2025 Faster Stochastic Optimization with Arbitrary Delays via Adaptive Asynchronous Mini-Batching ICML 2025 New Lower Bounds for Non-Convex Stochastic Optimization through Divergence Decomposition COLT 2025 Revisiting Convergence: Shuffling Complexity Beyond Lipschitz Smoothness ICML 2025 SERENA: A Unified Stochastic Recursive Variance Reduced Gradient Framework for Riemannian Non-Convex Optimization ICML 2025 Toward a Unified Theory of Gradient Descent under Generalized Smoothness ICML 2025 Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms ICML 2024 Faster Adaptive Decentralized Learning Algorithms ICML 2024 Generalization Analysis of Stochastic Weight Averaging with General Sampling ICML 2024 How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization ICML 2024 Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm ICML 2024 Locally Differentially Private Decentralized Stochastic Bilevel Optimization with Guaranteed Convergence Accuracy ICML 2024 Random Scaling and Momentum for Non-smooth Non-convex Optimization ICML 2024 Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features ICML 2024 Stochastic Optimization with Arbitrary Recurrent Data Sampling ICML 2024