stochastic gradient

Sample Efficient Stochastic Gradient Iterative Hard Thresholding Method for Stochastic Sparse Linear Regression with Limited Attribute Observation NeurIPS 2018 Stochastic Cubic Regularization for Fast Nonconvex Optimization NeurIPS 2018 Total stochastic gradient algorithms and applications in reinforcement learning NeurIPS 2018 Tracking the gradients using the Hessian: A new look at variance reducing stochastic methods AISTATS 2018 WHAI: Weibull Hybrid Autoencoding Inference for Deep Topic Modeling ICLR 2018 Zeroth-order (Non)-Convex Stochastic Optimization via Conditional Gradient and Gradient Updates NeurIPS 2018 A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms JMLR 2017 Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible ICML 2017 Conjugate-Computation Variational Inference : Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models AISTATS 2017 CPSG-MCMC: Clustering-Based Preprocessing method for Stochastic Gradient MCMC AISTATS 2017 Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC ICML 2017 Diffusion Approximations for Online Principal Component Estimation and Global Convergence NeurIPS 2017 Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization NeurIPS 2017 Exploiting Strong Convexity from Data with Primal-Dual First-Order Algorithms ICML 2017 Gradient Methods for Submodular Maximization NeurIPS 2017 High-Dimensional Variance-Reduced Stochastic Gradient Expectation-Maximization Algorithm ICML 2017 MEC: Memory-efficient Convolution for Deep Neural Network ICML 2017 Natasha: Faster Non-Convex Stochastic Optimization via Strongly Non-Convex Parameter ICML 2017 Non-convex Finite-Sum Optimization Via SCSG Methods NeurIPS 2017 Nonlinear Acceleration of Stochastic Algorithms NeurIPS 2017 Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms AISTATS 2017 SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient ICML 2017 Scalable Multi-Class Gaussian Process Classification using Expectation Propagation ICML 2017 Semi-supervised Max-margin Topic Model with Manifold Posterior Regularization IJCAI 2017 Sharp Minima Can Generalize For Deep Nets ICML 2017