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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

Evaluating the design space of diffusion-based generative models NIPS 2024
AsGrad: A Sharp Unified Analysis of Asynchronous-SGD Algorithms AISTATS 2024
Convergence of Message-Passing Graph Neural Networks with Generic Aggregation on Large Random Graphs JMLR 2024
Stability of Multi-Agent Learning in Competitive Networks: Delaying the Onset of Chaos AAAI 2024
CoVO-MPC: Theoretical analysis of sampling-based MPC and optimal covariance design L4DC 2024
Wasserstein convergence of Cech persistence diagrams for samplings of submanifolds NIPS 2024
Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence beyond the Minty Property AAAI 2024
A De-singularity Subgradient Approach for the Extended Weber Location Problem IJCAI 2024
Convergence guarantees for adaptive model predictive control with kinky inference L4DC 2024
Ordered Momentum for Asynchronous SGD NIPS 2024
Tending Towards Stability: Convergence Challenges in Small Language Models EMNLP 2024
A Boosting-Type Convergence Result for AdaBoost.MH with Factorized Multi-Class Classifiers NIPS 2024
How does PDE order affect the convergence of PINNs? NIPS 2024
Great Minds Think Alike: The Universal Convergence Trend of Input Salience NIPS 2024
Stochastic Methods in Variational Inequalities: Ergodicity, Bias and Refinements AISTATS 2024
Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts AISTATS 2024
An Analysis of Quantile Temporal-Difference Learning JMLR 2024
On the Unstable Convergence Regime of Gradient Descent AAAI 2024
Balance Reward and Safety Optimization for Safe Reinforcement Learning: A Perspective of Gradient Manipulation AAAI 2024
Unraveling the Gradient Descent Dynamics of Transformers NIPS 2024
Towards Robust Learning to Optimize with Theoretical Guarantees CVPR 2024
The Implicit Bias of Adam on Separable Data NIPS 2024
On the Convergence of an Adaptive Momentum Method for Adversarial Attacks AAAI 2024
Provably Convergent Federated Trilevel Learning AAAI 2024
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks JMLR 2024