stochastic method

Submodular Function Minimization with Noisy Evaluation Oracle NeurIPS 2019 Universal Approximation Property and Equivalence of Stochastic Computing-Based Neural Networks and Binary Neural Networks AAAI 2019 Approximate Bayesian Computation with Kullback-Leibler Divergence as Data Discrepancy AISTATS 2018 Direct Runge-Kutta Discretization Achieves Acceleration NeurIPS 2018 Horizon-Independent Minimax Linear Regression NeurIPS 2018 How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD NeurIPS 2018 Minimax Bounds on Stochastic Batched Convex Optimization COLT 2018 Minimizing Adaptive Regret with One Gradient per Iteration IJCAI 2018 On Markov Chain Gradient Descent NeurIPS 2018 Random Permutation Online Isotonic Regression NeurIPS 2017 Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning NeurIPS 2016 Sub-sampled Newton Methods with Non-uniform Sampling NeurIPS 2016 A Lower Bound for the Optimization of Finite Sums ICML 2015 Kullback-Leibler Proximal Variational Inference NeurIPS 2015 Exploiting easy data in online optimization NeurIPS 2014 Multiarmed Bandits With Limited Expert Advice COLT 2014 Parallel Direction Method of Multipliers NeurIPS 2014 One-Pass AUC Optimization ICML 2013 On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions ICML 2013 Stochastic Deconvolution CVPR 2013 Adaptive MCMC with Bayesian Optimization AISTATS 2012 Scalable nonconvex inexact proximal splitting NeurIPS 2012 Online Learning: Stochastic, Constrained, and Smoothed Adversaries NeurIPS 2011 TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning NeurIPS 2011 Elliptical slice sampling AISTATS 2010