stochastic process

Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems ICML 2015 Human Memory Search as Initial-Visit Emitting Random Walk NeurIPS 2015 Learning Theory and Algorithms for Forecasting Non-stationary Time Series NeurIPS 2015 Links Between Multiplicity Automata, Observable Operator Models and Predictive State Representations -- a Unified Learning Framework JMLR 2015 Online Optimization : Competing with Dynamic Comparators AISTATS 2015 Simple regret for infinitely many armed bandits ICML 2015 When are Kalman-Filter Restless Bandits Indexable? NeurIPS 2015 A* Sampling NeurIPS 2014 Efficient Continuous-Time Markov Chain Estimation ICML 2014 Hamiltonian Monte Carlo Without Detailed Balance ICML 2014 Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians ICML 2014 Memory (and Time) Efficient Sequential Monte Carlo ICML 2014 Nonparametric Bayesian inference on multivariate exponential families NeurIPS 2014 Rectangular Tiling Process ICML 2014 Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Hierarchical Models NeurIPS 2014 Achievability of Asymptotic Minimax Regret in Online and Batch Prediction ACML 2013 Analyzing Hogwild Parallel Gaussian Gibbs Sampling NeurIPS 2013 Computing the Stationary Distribution Locally NeurIPS 2013 Density estimation from unweighted k-nearest neighbor graphs: a roadmap NeurIPS 2013 How to Hedge an Option Against an Adversary: Black-Scholes Pricing is Minimax Optimal NeurIPS 2013 Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes AISTATS 2013 Locally Adaptive Bayesian Multivariate Time Series NeurIPS 2013 Lower Bounds and Selectivity of Weak-Consistent Policies in Stochastic Multi-Armed Bandit Problem JMLR 2013 Metastability for High-Dimensional Walking Systems on Stochastically Rough Terrain RSS 2013 Predictive PAC Learning and Process Decompositions NeurIPS 2013