stochastic process

Tracking the Evolution of Customer Purchase Behavior Segmentation via a Fragmentation-Coagulation Process IJCAI 2017 Uncovering Causality from Multivariate Hawkes Integrated Cumulants ICML 2017 Variational Walkback: Learning a Transition Operator as a Stochastic Recurrent Net NeurIPS 2017 A Variational Analysis of Stochastic Gradient Algorithms ICML 2016 Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition NeurIPS 2016 Combinatorial semi-bandit with known covariance NeurIPS 2016 Completely random measures for modelling block-structured sparse networks NeurIPS 2016 Consistent Kernel Mean Estimation for Functions of Random Variables NeurIPS 2016 Early Stopping as Nonparametric Variational Inference AISTATS 2016 Edge-exchangeable graphs and sparsity NeurIPS 2016 Fast learning rates with heavy-tailed losses NeurIPS 2016 Isotonic Hawkes Processes ICML 2016 Learning Population-Level Diffusions with Generative RNNs ICML 2016 On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes AISTATS 2016 Probabilistic Linear Multistep Methods NeurIPS 2016 Reconstructing Parameters of Spreading Models from Partial Observations NeurIPS 2016 Simulation and Calibration of a Fully Bayesian Marked Multidimensional Hawkes Process with Dissimilar Decays ACML 2016 Spectral Learning of Dynamic Systems from Nonequilibrium Data NeurIPS 2016 Universal Approximation Results for the Temporal Restricted Boltzmann Machine and the Recurrent Temporal Restricted Boltzmann Machine JMLR 2016 Adaptive Online Learning NeurIPS 2015 Adaptive Stochastic Optimization: From Sets to Paths NeurIPS 2015 Anytime Influence Bounds and the Explosive Behavior of Continuous-Time Diffusion Networks NeurIPS 2015 A Spatiotemporal Optimal Stopping Problem for Mission Monitoring with Stationary Viewpoints RSS 2015 Cornering Stationary and Restless Mixing Bandits with Remix-UCB NeurIPS 2015 Exponential Integration for Hamiltonian Monte Carlo ICML 2015