convergence bound

A Non-Asymptotic Convergent Analysis for Scored-Based Graph Generative Model via a System of Stochastic Differential Equations ICML 2025 GAS: Generative Activation-Aided Asynchronous Split Federated Learning AAAI 2025 Locally Optimal Descent for Dynamic Stepsize Scheduling AISTATS 2025 Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics ICLR 2025 Provable Convergence Bounds for Hybrid Dynamical Sampling and Optimization ICLR 2025 Hierarchical Federated Learning with Multi-Timescale Gradient Correction NeurIPS 2024 Nearly d-Linear Convergence Bounds for Diffusion Models via Stochastic Localization ICLR 2024 Sharp analysis of power iteration for tensor PCA JMLR 2024 Tighter Convergence Bounds for Shuffled SGD via Primal-Dual Perspective NeurIPS 2024 Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions ICML 2023 Mini-batch k-means terminates within O(d/ε) iterations ICLR 2023 On the convergence of the MLE as an estimator of the learning rate in the Exp3 algorithm ICML 2023 Bounding the Error of Discretized Langevin Algorithms for Non-Strongly Log-Concave Targets JMLR 2022 Improved Convergence Rates for Sparse Approximation Methods in Kernel-Based Learning ICML 2022 Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond ICLR 2022 Nearly Tight Convergence Bounds for Semi-discrete Entropic Optimal Transport AISTATS 2022 Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent AAAI 2021 Bounding the expected run-time of nonconvex optimization with early stopping UAI 2020 Complexity Guarantees for Polyak Steps with Momentum COLT 2020 Shared Autonomy with Learned Latent Actions RSS 2020 Dimension-Free Bounds for Low-Precision Training NeurIPS 2019 First-Order Adaptive Sample Size Methods to Reduce Complexity of Empirical Risk Minimization NeurIPS 2017 On the Rate of Convergence and Error Bounds for LSTD(λ) ICML 2015 The Perturbed Variation NeurIPS 2012 Bundle Methods for Machine Learning NeurIPS 2007