Stochastic Processes

Riffled Independence for Ranked Data NeurIPS 2009 Sensitivity analysis in HMMs with application to likelihood maximization NeurIPS 2009 Stable and Efficient Gaussian Process Calculations JMLR 2009 Time-rescaling methods for the estimation and assessment of non-Poisson neural encoding models NeurIPS 2009 A Convergent $O(n)$ Temporal-difference Algorithm for Off-policy Learning with Linear Function Approximation NeurIPS 2008 Cell Assemblies in Large Sparse Inhibitory Networks of Biologically Realistic Spiking Neurons NeurIPS 2008 Efficient Sampling for Gaussian Process Inference using Control Variables NeurIPS 2008 Finite-Time Bounds for Fitted Value Iteration JMLR 2008 HyPE: Hybrid Particle-Element Approach for Recursive Bayesian Searching and Tracking RSS 2008 Kernel Measures of Independence for non-iid Data NeurIPS 2008 Metastable Walking on Stochastically Rough Terrain RSS 2008 Modeling the effects of memory on human online sentence processing with particle filters NeurIPS 2008 Multi-Agent Filtering with Infinitely Nested Beliefs NeurIPS 2008 Nonparametric Bayesian Learning of Switching Linear Dynamical Systems NeurIPS 2008 Optimal Response Initiation: Why Recent Experience Matters NeurIPS 2008 Particle Filter-based Policy Gradient in POMDPs NeurIPS 2008 Rademacher Complexity Bounds for Non-I.I.D. Processes NeurIPS 2008 Short-Term Depression in VLSI Stochastic Synapse NeurIPS 2008 Stochastic Recruitment: A Limited-Feedback Control Policy for Large Ensemble Systems RSS 2008 The Mondrian Process NeurIPS 2008 Value Function Based Reinforcement Learning in Changing Markovian Environments JMLR 2008 Adaptive Online Gradient Descent NeurIPS 2007 Collective Inference on Markov Models for Modeling Bird Migration NeurIPS 2007 Continuous Time Particle Filtering for fMRI NeurIPS 2007 Inferring Elapsed Time from Stochastic Neural Processes NeurIPS 2007