convergence analysis

394 papers

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stochastic gradient descent (1088) convergence rate (606) stochastic optimization (1060) non-convex optimization (546) gradient descent (1143) federated learning (1320) neural network optimization (1293) reinforcement learning (4122) distributed learning (563) neural network (6616)

Papers

Momentum Ensures Convergence of SIGNSGD under Weaker Assumptions ICML 2023

Large data limit of the MBO scheme for data clustering: convergence of the dynamics JMLR 2023

Performative Reinforcement Learning ICML 2023

On the Convergence of Black-Box Variational Inference NIPS 2023

Scale Invariant Power Iteration JMLR 2023

A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates JMLR 2023

Convergence of Adam Under Relaxed Assumptions NIPS 2023

Accelerated Stochastic Optimization Methods under Quasar-convexity ICML 2023

Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity ICML 2023

Competitive Gradient Optimization ICML 2023

Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions NIPS 2023

On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $\epsilon$-Greedy Exploration NIPS 2023

On the Convergence of Stochastic Gradient Descent with Bandwidth-based Step Size JMLR 2023

Asynchronous Iterations in Optimization: New Sequence Results and Sharper Algorithmic Guarantees JMLR 2023

GANs as Gradient Flows that Converge JMLR 2023

Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction NIPS 2023

FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks ICML 2023

On the Training Instability of Shuffling SGD with Batch Normalization ICML 2023

Federated Adversarial Learning: A Framework with Convergence Analysis ICML 2023

Convergence of Alternating Gradient Descent for Matrix Factorization NIPS 2023

Convergence Analysis of Sequential Federated Learning on Heterogeneous Data NIPS 2023

On the Convergence of Federated Averaging with Cyclic Client Participation ICML 2023

Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss ICML 2023

Convergence of Actor-Critic with Multi-Layer Neural Networks NIPS 2023

Coordinate Descent Methods for Fractional Minimization ICML 2023