stochastic gradient descent

On Biased Compression for Distributed Learning JMLR 2023 On Learning Rates and Schrödinger Operators JMLR 2023 Online Heavy-tailed Change-point detection UAI 2023 Online robust non-stationary estimation NeurIPS 2023 Online Stochastic Gradient Descent with Arbitrary Initialization Solves Non-smooth, Non-convex Phase Retrieval JMLR 2023 On Single-Index Models beyond Gaussian Data NeurIPS 2023 On the Convergence of Black-Box Variational Inference NeurIPS 2023 On the Convergence of Stochastic Gradient Descent with Bandwidth-based Step Size JMLR 2023 On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms NeurIPS 2023 On the Stability and Generalization of Triplet Learning AAAI 2023 On the Training Instability of Shuffling SGD with Batch Normalization ICML 2023 Opposite Online Learning via Sequentially Integrated Stochastic Gradient Descent Estimators AAAI 2023 Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization NeurIPS 2023 Phase diagram of early training dynamics in deep neural networks: effect of the learning rate, depth, and width NeurIPS 2023 “Plus/minus the learning rate”: Easy and Scalable Statistical Inference with SGD AISTATS 2023 Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference ICML 2023 Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima NeurIPS 2023 Random Reshuffling with Variance Reduction: New Analysis and Better Rates UAI 2023 Recursive Quantile Estimation: Non-Asymptotic Confidence Bounds JMLR 2023 Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD JMLR 2023 Resetting the Optimizer in Deep RL: An Empirical Study NeurIPS 2023 Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees ICML 2023 Robust Collaborative Learning with Linear Gradient Overhead ICML 2023 Robust Linear Regression for General Feature Distribution AISTATS 2023 Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent NeurIPS 2023