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stochastic gradient

296 papers

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Also known as

SGVB SVRG SGHMC SGLD SG SGMCMC SGD

Co-occurring keywords

variance reduction (520) markov chain monte carlo (724) stochastic optimization (1060) bayesian inference (1904) stochastic gradient descent (1088) convex optimization (1320) nonconvex optimization (316) convergence rate (606) langevin dynamics (128) variational inference (2069)

Papers

Mini-batching error and adaptive Langevin dynamics JMLR 2023
Online Learning for Non-monotone DR-Submodular Maximization: From Full Information to Bandit Feedback AISTATS 2023
Optimal Preconditioning and Fisher Adaptive Langevin Sampling NIPS 2023
Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization AAAI 2023
Riemannian stochastic optimization methods avoid strict saddle points NIPS 2023
On the Overlooked Structure of Stochastic Gradients NIPS 2023
Tighter Analysis for ProxSkip ICML 2023
Exploiting Inferential Structure in Neural Processes UAI 2023
A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial Participation Setting NIPS 2023
A Variance-Reduced and Stabilized Proximal Stochastic Gradient Method with Support Identification Guarantees for Structured Optimization AISTATS 2023
Stochastic Gradient Succeeds for Bandits ICML 2023
Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data ICML 2023
Knowledge Distillation Performs Partial Variance Reduction NIPS 2023
Policy Gradient Play with Networked Agents in Markov Potential Games L4DC 2023
Unbiased Compression Saves Communication in Distributed Optimization: When and How Much? NIPS 2023
Amortized Proximal Optimization NIPS 2022
Generalizing Gaussian Smoothing for Random Search ICML 2022
Adaptive Random Walk Gradient Descent for Decentralized Optimization ICML 2022
On the Convergence of Stochastic Multi-Objective Gradient Manipulation and Beyond NIPS 2022
Structured Stochastic Gradient MCMC ICML 2022
Faster One-Sample Stochastic Conditional Gradient Method for Composite Convex Minimization AISTATS 2022
Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective ICML 2022
Efficient Variance Reduction for Meta-learning ICML 2022
On Sample Optimality in Personalized Collaborative and Federated Learning NIPS 2022
Gradient-Free Method for Heavily Constrained Nonconvex Optimization ICML 2022