stochastic gradient

A Complete Recipe for Stochastic Gradient MCMC NeurIPS 2015 Adding vs. Averaging in Distributed Primal-Dual Optimization ICML 2015 A Stochastic PCA and SVD Algorithm with an Exponential Convergence Rate ICML 2015 Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling NeurIPS 2015 Exponential Integration for Hamiltonian Monte Carlo ICML 2015 Learning Wake-Sleep Recurrent Attention Models NeurIPS 2015 Learning with Incremental Iterative Regularization NeurIPS 2015 Local Expectation Gradients for Black Box Variational Inference NeurIPS 2015 Markov Chain Monte Carlo and Variational Inference: Bridging the Gap ICML 2015 Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields AISTATS 2015 Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo ICML 2015 Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients NeurIPS 2015 StopWasting My Gradients: Practical SVRG NeurIPS 2015 Variational Dropout and the Local Reparameterization Trick NeurIPS 2015 Bayesian Sampling Using Stochastic Gradient Thermostats NeurIPS 2014 Black Box Variational Inference AISTATS 2014 Distributed Stochastic Gradient MCMC ICML 2014 SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives NeurIPS 2014 Scalable Kernel Methods via Doubly Stochastic Gradients NeurIPS 2014 Smoothed Gradients for Stochastic Variational Inference NeurIPS 2014 Stochastic Gradient Hamiltonian Monte Carlo ICML 2014 Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions NeurIPS 2013 Linear Convergence with Condition Number Independent Access of Full Gradients NeurIPS 2013 Stochastic Gradient Riemannian Langevin Dynamics on the Probability Simplex NeurIPS 2013 Stochastic Optimization of PCA with Capped MSG NeurIPS 2013