stochastic gradient

Stochastic Gradient Trees ACML 2019 Towards closing the gap between the theory and practice of SVRG NeurIPS 2019 Understanding the Role of Momentum in Stochastic Gradient Methods NeurIPS 2019 Variance Reduction for Matrix Games NeurIPS 2019 Variational Training for Large-Scale Noisy-OR Bayesian Networks UAI 2019 Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization IJCAI 2019 A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization NeurIPS 2018 ATOMO: Communication-efficient Learning via Atomic Sparsification NeurIPS 2018 Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters NeurIPS 2018 Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients ICML 2018 Dissipativity Theory for Accelerating Stochastic Variance Reduction: A Unified Analysis of SVRG and Katyusha Using Semidefinite Programs ICML 2018 Efficient Stochastic Gradient Hard Thresholding NeurIPS 2018 Gaussian Process Prior Variational Autoencoders NeurIPS 2018 Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization NeurIPS 2018 Global Non-convex Optimization with Discretized Diffusions NeurIPS 2018 Gradient Sparsification for Communication-Efficient Distributed Optimization NeurIPS 2018 LAG: Lazily Aggregated Gradient for Communication-Efficient Distributed Learning NeurIPS 2018 Large-Scale Stochastic Sampling from the Probability Simplex NeurIPS 2018 Learning To Learn Around A Common Mean NeurIPS 2018 Online Learning with Non-Convex Losses and Non-Stationary Regret AISTATS 2018 On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo ICML 2018 Projection-Free Online Optimization with Stochastic Gradient: From Convexity to Submodularity ICML 2018 Quasi-Monte Carlo Variational Inference ICML 2018 Regularizing and Optimizing LSTM Language Models ICLR 2018 Riemannian Stochastic Recursive Gradient Algorithm ICML 2018