Stochastic Processes

Markov Chain Monte Carlo with People NeurIPS 2007 Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression NeurIPS 2007 Privacy-Preserving Belief Propagation and Sampling NeurIPS 2007 Sequential Hypothesis Testing under Stochastic Deadlines NeurIPS 2007 The rat as particle filter NeurIPS 2007 Variational Inference for Diffusion Processes NeurIPS 2007 Variational inference for Markov jump processes NeurIPS 2007 A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems NeurIPS 2006 Bayesian Policy Gradient Algorithms NeurIPS 2006 Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems JMLR 2006 Geometric Variance Reduction in Markov Chains: Application to Value Function and Gradient Estimation JMLR 2006 iLSTD: Eligibility Traces and Convergence Analysis NeurIPS 2006 Optimal Change-Detection and Spiking Neurons NeurIPS 2006 Step Size Adaptation in Reproducing Kernel Hilbert Space JMLR 2006 Temporal dynamics of information content carried by neurons in the primary visual cortex NeurIPS 2006 The Iterated Sigma Point Kalman Filter with Applications to Long Range Stereo RSS 2006 Dynamic Maps for Long-Term Operation of Mobile Service Robots RSS 2005 Gaussian Processes for Ordinal Regression JMLR 2005 Reinforcement Learning with Factored States and Actions JMLR 2004 A Generative Model for Separating Illumination and Reflectance from Images JMLR 2003 FINkNN: A Fuzzy Interval Number k-Nearest Neighbor Classifier for Prediction of Sugar Production from Populations of Samples JMLR 2003 Statistical Dynamics of On-line Independent Component Analysis JMLR 2003 Tree-Structured Neural Decoding JMLR 2003