Stochastic Processes

On Model Stability as a Function of Random Seed CoNLL 2019 On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization IJCAI 2019 On the statistical rate of nonlinear recovery in generative models with heavy-tailed data ICML 2019 Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards ICML 2019 Optimal Best Markovian Arm Identification with Fixed Confidence NeurIPS 2019 Optimal Exploitation of Clustering and History Information in Multi-armed Bandit IJCAI 2019 Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile ICLR 2019 Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models ICML 2019 Parameter elimination in particle Gibbs sampling NeurIPS 2019 Parameter-Free Online Convex Optimization with Sub-Exponential Noise COLT 2019 Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models ICML 2019 Pathwise Derivatives for Multivariate Distributions AISTATS 2019 Planning with State Abstractions for Non-Markovian Task Specifications RSS 2019 PointFlow: 3D Point Cloud Generation With Continuous Normalizing Flows ICCV 2019 Poisson-Minibatching for Gibbs Sampling with Convergence Rate Guarantees NeurIPS 2019 Predicting Sick Patient Volume in a Pediatric Outpatient Setting using Time Series Analysis MLHC 2019 Privacy Amplification by Mixing and Diffusion Mechanisms NeurIPS 2019 Private Stochastic Convex Optimization with Optimal Rates NeurIPS 2019 Quantifying Uncertainty in Online Regression Forests JMLR 2019 Rapid Convergence of the Unadjusted Langevin Algorithm: Isoperimetry Suffices NeurIPS 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 Regularized Contextual Bandits AISTATS 2019 Robust Online Matching with User Arrival Distribution Drift AAAI 2019