Stochastic Processes

Logistic Markov Decision Processes IJCAI 2017 Log-normality and Skewness of Estimated State/Action Values in Reinforcement Learning NeurIPS 2017 Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization COLT 2017 Markov Chain Truncation for Doubly-Intractable Inference AISTATS 2017 Max-value Entropy Search for Efficient Bayesian Optimization ICML 2017 Measuring Sample Quality with Kernels ICML 2017 Mini-batch Block-coordinate based Stochastic Average Adjusted Gradient Methods to Solve Big Data Problems ACML 2017 Model evidence from nonequilibrium simulations NeurIPS 2017 Multi-Modal Mean-Fields via Cardinality-Based Clamping CVPR 2017 Multi-Objective Non-parametric Sequential Prediction NeurIPS 2017 Multiple Sound Source Counting and Localization Based on Spatial Principal Eigenvector Interspeech 2017 Nearly Optimal Sampling Algorithms for Combinatorial Pure Exploration COLT 2017 Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis COLT 2017 On Equivalence of Martingale Tail Bounds and Deterministic Regret Inequalities COLT 2017 Online Convex Optimization with Stochastic Constraints NeurIPS 2017 Online Learning for Multivariate Hawkes Processes NeurIPS 2017 On Markov chain Monte Carlo methods for tall data JMLR 2017 On the Propagation of Low-Rate Measurement Error to Subgraph Counts in Large Networks JMLR 2017 On Thompson Sampling and Asymptotic Optimality IJCAI 2017 Parameter identification in Markov chain choice models ALT 2017 Particle Gibbs Split-Merge Sampling for Bayesian Inference in Mixture Models JMLR 2017 Predicting User Activity Level In Point Processes With Mass Transport Equation NeurIPS 2017 Probabilistic Completeness of Randomized Possibility Graphs Applied to Bipedal Walking in Semi-unstructured Environments RSS 2017 Probabilistic Line Searches for Stochastic Optimization JMLR 2017 Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models NeurIPS 2017