Stochastic Processes

Spike train entropy-rate estimation using hierarchical Dirichlet process priors NeurIPS 2013 Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes ICML 2013 Stochastic Variational Inference JMLR 2013 Thompson Sampling for 1-Dimensional Exponential Family Bandits NeurIPS 2013 Top-down particle filtering for Bayesian decision trees ICML 2013 Topology-Constrained Layered Tracking with Latent Flow ICCV 2013 Toward Optimal Stratification for Stratified Monte-Carlo Integration ICML 2013 Tracking Time-varying Graphical Structure NeurIPS 2013 Adaptive Metropolis with Online Relabeling AISTATS 2012 A Marginalized Particle Gaussian Process Regression NeurIPS 2012 An Autoregressive Approach to Nonparametric Hierarchical Dependent Modeling AISTATS 2012 Ancestor Sampling for Particle Gibbs NeurIPS 2012 Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled button NeurIPS 2012 Bayesian Inference for Change Points in Dynamical Systems with Reusable States - a Chinese Restaurant Process Approach AISTATS 2012 Compressive neural representation of sparse, high-dimensional probabilities NeurIPS 2012 Delay Compensation with Dynamical Synapses NeurIPS 2012 Effective Split-Merge Monte Carlo Methods for Nonparametric Models of Sequential Data NeurIPS 2012 Efficient high dimensional maximum entropy modeling via symmetric partition functions NeurIPS 2012 Entangled Monte Carlo NeurIPS 2012 Entropy Search for Information-Efficient Global Optimization JMLR 2012 Evaluation of marginal likelihoods via the density of states AISTATS 2012 Finite Sample Convergence Rates of Zero-Order Stochastic Optimization Methods NeurIPS 2012 Flexible Martingale Priors for Deep Hierarchies AISTATS 2012 Forward-Backward Activation Algorithm for Hierarchical Hidden Markov Models NeurIPS 2012 Infinite-Dimensional Kalman Filtering Approach to Spatio-Temporal Gaussian Process Regression AISTATS 2012