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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

High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm ICML 2017
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient ICML 2017
A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms JMLR 2017
Gradient Methods for Submodular Maximization NIPS 2017
Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization NIPS 2017
Nonlinear Acceleration of Stochastic Algorithms NIPS 2017
CPSG-MCMC: Clustering-Based Preprocessing method for Stochastic Gradient MCMC AISTATS 2017
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation ICML 2017
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms AISTATS 2017
Semi-supervised Max-margin Topic Model with Manifold Posterior Regularization IJCAI 2017
Variational Inference for Gaussian Process Models with Linear Complexity NIPS 2017
Non-convex Finite-Sum Optimization Via SCSG Methods NIPS 2017
Conjugate-Computation Variational Inference : Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models AISTATS 2017
Diffusion Approximations for Online Principal Component Estimation and Global Convergence NIPS 2017
MEC: Memory-efficient Convolution for Deep Neural Network ICML 2017
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC ICML 2017
Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms ICML 2017
Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible ICML 2017
Stochastic Gradient Monomial Gamma Sampler ICML 2017
Stochastic Quasi-Newton Langevin Monte Carlo ICML 2016
Matrix Eigen-decomposition via Doubly Stochastic Riemannian Optimization ICML 2016
Stochastic Variational Deep Kernel Learning NIPS 2016
Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization NIPS 2016
On Graduated Optimization for Stochastic Non-Convex Problems ICML 2016
Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient ICML 2016