stochastic gradient

Efficient Variance Reduction for Meta-learning ICML 2022 Fast Distributionally Robust Learning with Variance-Reduced Min-Max Optimization AISTATS 2022 Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization AISTATS 2022 Faster Perturbed Stochastic Gradient Methods for Finding Local Minima ALT 2022 FedNest: Federated Bilevel, Minimax, and Compositional Optimization ICML 2022 Generalizing Gaussian Smoothing for Random Search ICML 2022 Gradient-Free Method for Heavily Constrained Nonconvex Optimization ICML 2022 Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients NeurIPS 2022 Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective ICML 2022 Noisy Riemannian Gradient Descent for Eigenvalue Computation with Application to Inexact Stochastic Recursive Gradient Algorithm ACML 2022 Nonlinear Sufficient Dimension Reduction with a Stochastic Neural Network NeurIPS 2022 On Biased Stochastic Gradient Estimation JMLR 2022 On Sample Optimality in Personalized Collaborative and Federated Learning NeurIPS 2022 On the Convergence of Stochastic Multi-Objective Gradient Manipulation and Beyond NeurIPS 2022 QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning AISTATS 2022 Reproducibility in Optimization: Theoretical Framework and Limits NeurIPS 2022 Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization NeurIPS 2022 Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold JMLR 2022 Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization NeurIPS 2022 Scalable One-Pass Optimisation of High-Dimensional Weight-Update Hyperparameters by Implicit Differentiation ICLR 2022 Structured Stochastic Gradient MCMC ICML 2022 Variance Reduced EXTRA and DIGing and Their Optimal Acceleration for Strongly Convex Decentralized Optimization JMLR 2022 Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities AAAI 2021 A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method AAAI 2021 A Hybrid Variance-Reduced Method for Decentralized Stochastic Non-Convex Optimization ICML 2021