Stochastic Processes

Robust Gradient-Based Markov Subsampling AAAI 2020 Robustness of Community Detection to Random Geometric Perturbations NeurIPS 2020 Robust Optimisation Monte Carlo AISTATS 2020 Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack AAAI 2020 Safe Linear Stochastic Bandits AAAI 2020 Sampling from a k-DPP without looking at all items NeurIPS 2020 Scalable Belief Propagation via Relaxed Scheduling NeurIPS 2020 Scalable Gradients for Stochastic Differential Equations AISTATS 2020 Scalable Uncertainty for Computer Vision With Functional Variational Inference CVPR 2020 SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates ICML 2020 Sequential Cooperative Bayesian Inference ICML 2020 SEVIR : A Storm Event Imagery Dataset for Deep Learning Applications in Radar and Satellite Meteorology NeurIPS 2020 Shoreline: Data-Driven Threshold Estimation of Online Reserves of Cryptocurrency Trading Platforms AAAI 2020 Simultaneous Inference for Massive Data: Distributed Bootstrap ICML 2020 Slice Sampling for General Completely Random Measures UAI 2020 Sparse Spectrum Warped Input Measures for Nonstationary Kernel Learning NeurIPS 2020 Stable behaviour of infinitely wide deep neural networks AISTATS 2020 Statistical and Neural Network Based Speech Activity Detection in Non-Stationary Acoustic Environments Interspeech 2020 Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits NeurIPS 2020 Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions AISTATS 2020 Stein Variational Inference for Discrete Distributions AISTATS 2020 Stochastically Dominant Distributional Reinforcement Learning ICML 2020 Stochastic Flows and Geometric Optimization on the Orthogonal Group ICML 2020 Stochastic Gradient and Langevin Processes ICML 2020 Stochastic Gradient Descent in Correlated Settings: A Study on Gaussian Processes NeurIPS 2020