Stochastic Processes

Interference and Generalization in Temporal Difference Learning ICML 2020 Involutive MCMC: a Unifying Framework ICML 2020 Is Big Data Performance Reproducible in Modern Cloud Networks? NSDI 2020 Iterative Context-Aware Graph Inference for Visual Dialog CVPR 2020 Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning ICLR 2020 Langevin Monte Carlo without smoothness AISTATS 2020 Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes AISTATS 2020 Learning Kernel Tests Without Data Splitting NeurIPS 2020 Likelihood-free MCMC with Amortized Approximate Ratio Estimators ICML 2020 Localized Learning of Robust Controllers for Networked Systems with Dynamic Topology L4DC 2020 Localizing and Amortizing: Efficient Inference for Gaussian Processes ACML 2020 Low Bias Low Variance Gradient Estimates for Boolean Stochastic Networks ICML 2020 LSGCN: Long Short-Term Traffic Prediction with Graph Convolutional Networks IJCAI 2020 Making Sense of Reinforcement Learning and Probabilistic Inference ICLR 2020 Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes NeurIPS 2020 Minibatch vs Local SGD for Heterogeneous Distributed Learning NeurIPS 2020 Mixed Hamiltonian Monte Carlo for Mixed Discrete and Continuous Variables NeurIPS 2020 Mixing Time Estimation in Ergodic Markov Chains from a Single Trajectory with Contraction Methods ALT 2020 Model and Reinforcement Learning for Markov Games with Risk Preferences AAAI 2020 Model-Augmented Conditional Mutual Information Estimation for Feature Selection UAI 2020 Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes ICML 2020 Modelling Suspense in Short Stories as Uncertainty Reduction over Neural Representation ACL 2020 Model Selection in Contextual Stochastic Bandit Problems NeurIPS 2020 Momentum-Based Policy Gradient Methods ICML 2020 Momentum Improves Normalized SGD ICML 2020