Skip to content
conftrace_

convergence guarantee

247 papers

Explore in graph

Co-occurring keywords · papers mentioning both

stochastic gradient descent (29) non-convex optimization (27) gradient descent (24) stochastic optimization (23) federated learning (21) convergence analysis (16) reinforcement learning (16) neural network (10) neural network optimization (10) temporal difference learning (10)

Papers

BOBA: Byzantine-Robust Federated Learning with Label Skewness AISTATS 2024 Communication-Efficient Federated Learning With Data and Client Heterogeneity AISTATS 2024 ControlSynth Neural ODEs: Modeling Dynamical Systems with Guaranteed Convergence NeurIPS 2024 Convergence of Gradient Descent with Small Initialization for Unregularized Matrix Completion COLT 2024 Convergence of Message-Passing Graph Neural Networks with Generic Aggregation on Large Random Graphs JMLR 2024 Countering the Communication Bottleneck in Federated Learning: A Highly Efficient Zero-Order Optimization Technique JMLR 2024 Dropout Enhanced Bilevel Training ICLR 2024 Enhancing Efficiency of Safe Reinforcement Learning via Sample Manipulation NeurIPS 2024 Fair Resource Allocation in Multi-Task Learning ICML 2024 Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity Allocation with Global Constraint in Minutes AAAI 2024 FedAST: Federated Asynchronous Simultaneous Training UAI 2024 FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees ICML 2024 Fine-grained Analysis of Stability and Generalization for Stochastic Bilevel Optimization IJCAI 2024 Gradient-based Discrete Sampling with Automatic Cyclical Scheduling NeurIPS 2024 Heterogeneous-Agent Reinforcement Learning JMLR 2024 High Probability Convergence Bounds for Non-convex Stochastic Gradient Descent with Sub-Weibull Noise JMLR 2024 Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds ICML 2024 Local and Adaptive Mirror Descents in Extensive-Form Games NeurIPS 2024 Loss Landscape Characterization of Neural Networks without Over-Parametrization NeurIPS 2024 MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence NeurIPS 2024 On Convergence of Incremental Gradient for Non-convex Smooth Functions ICML 2024 On the convergence of adaptive first order methods: Proximal gradient and alternating minimization algorithms L4DC 2024 Performative Reinforcement Learning in Gradually Shifting Environments UAI 2024 Physics-Informed Neural Network Policy Iteration: Algorithms, Convergence, and Verification ICML 2024 Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guarantees NeurIPS 2024