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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

Accelerating Relative Entropy Coding with Space Partitioning NIPS 2024
Byzantine Robustness and Partial Participation Can Be Achieved at Once: Just Clip Gradient Differences NIPS 2024
Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions NIPS 2024
B-ary Tree Push-Pull Method is Provably Efficient for Distributed Learning on Heterogeneous Data NIPS 2024
Penalized Overdamped and Underdamped Langevin Monte Carlo Algorithms for Constrained Sampling JMLR 2024
Compressed and distributed least-squares regression: convergence rates with applications to federated learning JMLR 2024
PROMISE: Preconditioned Stochastic Optimization Methods by Incorporating Scalable Curvature Estimates JMLR 2024
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets JMLR 2024
Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling NIPS 2024
Nesterov acceleration despite very noisy gradients NIPS 2024
Improving the Worst-Case Bidirectional Communication Complexity for Nonconvex Distributed Optimization under Function Similarity NIPS 2024
Lower Bounds and Accelerated Algorithms for Bilevel Optimization JMLR 2023
A Mini-Block Fisher Method for Deep Neural Networks AISTATS 2023
Accelerated Zeroth-order Method for Non-Smooth Stochastic Convex Optimization Problem with Infinite Variance NIPS 2023
Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards NIPS 2023
On the Convergence of Distributed Stochastic Bilevel Optimization Algorithms over a Network AISTATS 2023
Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels ICML 2023
Blockwise Stochastic Variance-Reduced Methods with Parallel Speedup for Multi-Block Bilevel Optimization ICML 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities NIPS 2023
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis NIPS 2023
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization ICML 2023
Exploiting Inferential Structure in Neural Processes UAI 2023
Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data ICML 2023
Online Learning for Non-monotone DR-Submodular Maximization: From Full Information to Bandit Feedback AISTATS 2023
Stochastic Gradient Succeeds for Bandits ICML 2023