stochastic optimization

Online Factorization and Partition of Complex Networks by Random Walk UAI 2019 Online Forecasting of Total-Variation-bounded Sequences NeurIPS 2019 Online Variance Reduction with Mixtures ICML 2019 On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization ICLR 2019 On the convergence of single-call stochastic extra-gradient methods NeurIPS 2019 On the Ineffectiveness of Variance Reduced Optimization for Deep Learning NeurIPS 2019 On the Optimality of Perturbations in Stochastic and Adversarial Multi-armed Bandit Problems NeurIPS 2019 On the optimality of the Hedge algorithm in the stochastic regime JMLR 2019 Optimal Minimization of the Sum of Three Convex Functions with a Linear Operator AISTATS 2019 Optimal Stochastic and Online Learning with Individual Iterates NeurIPS 2019 Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile ICLR 2019 PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits ICML 2019 Perturbed-History Exploration in Stochastic Multi-Armed Bandits IJCAI 2019 Polynomial Cost of Adaptation for X-Armed Bandits NeurIPS 2019 Proximal Splitting Meets Variance Reduction AISTATS 2019 Pyro: Deep Universal Probabilistic Programming JMLR 2019 Reachable Space Characterization of Markov Decision Processes with Time Variability RSS 2019 Recovering Bandits NeurIPS 2019 Reducing the variance in online optimization by transporting past gradients NeurIPS 2019 Reparameterizable Subset Sampling via Continuous Relaxations IJCAI 2019 Scalable Approximations for Generalized Linear Problems JMLR 2019 Scalable Collapsed Inference for High-Dimensional Topic Models NAACL 2019 Scalable Training of Inference Networks for Gaussian-Process Models ICML 2019 Sever: A Robust Meta-Algorithm for Stochastic Optimization ICML 2019 Singleshot : a scalable Tucker tensor decomposition NeurIPS 2019