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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

Quasi-Monte Carlo Quasi-Newton in Variational Bayes JMLR 2021
A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models AISTATS 2021
Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo JMLR 2021
Langevin Monte Carlo: random coordinate descent and variance reduction JMLR 2021
Fractional moment-preserving initialization schemes for training deep neural networks AISTATS 2021
Finding First-Order Nash Equilibria of Zero-Sum Games with the Regularized Nikaido-Isoda Function AISTATS 2021
Learning with risk-averse feedback under potentially heavy tails AISTATS 2021
Replica Exchange for Non-Convex Optimization JMLR 2021
Learning from Censored and Dependent Data: The case of Linear Dynamics COLT 2021
Projected Stochastic Gradient Langevin Algorithms for Constrained Sampling and Non-Convex Learning COLT 2021
MetaGrad: Adaptation using Multiple Learning Rates in Online Learning JMLR 2021
Federated stochastic gradient Langevin dynamics UAI 2021
Secure Deep Graph Generation with Link Differential Privacy IJCAI 2021
Riemannian Stochastic Recursive Momentum Method for non-Convex Optimization IJCAI 2021
A Stochastic Newton Algorithm for Distributed Convex Optimization NIPS 2021
Dynamics of Stochastic Momentum Methods on Large-scale, Quadratic Models NIPS 2021
EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback NIPS 2021
Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems NIPS 2021
Optimal Underdamped Langevin MCMC Method NIPS 2021
A Hybrid Variance-Reduced Method for Decentralized Stochastic Non-Convex Optimization ICML 2021
Distributed Saddle-Point Problems Under Data Similarity NIPS 2021
Differentiable Annealed Importance Sampling and the Perils of Gradient Noise NIPS 2021
Sample Efficient Reinforcement Learning with REINFORCE AAAI 2021
Three Operator Splitting with Subgradients, Stochastic Gradients, and Adaptive Learning Rates NIPS 2021
Understanding the Effect of Stochasticity in Policy Optimization NIPS 2021