Stochastic Processes

An Application of Tree-Structured Expectation Propagation for Channel Decoding NeurIPS 2011 Directional Statistics on Permutations AISTATS 2011 Dynamical segmentation of single trials from population neural data NeurIPS 2011 Empirical models of spiking in neural populations NeurIPS 2011 Estimating beta-mixing coefficients AISTATS 2011 Estimating Diffusion Probability Changes for AsIC-SIS Model from Information Diffusion Results ACML 2011 From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models NeurIPS 2011 Gaussian process modulated renewal processes NeurIPS 2011 Gaussian Process Training with Input Noise NeurIPS 2011 Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent NeurIPS 2011 Improved Algorithms for Linear Stochastic Bandits NeurIPS 2011 Inference in continuous-time change-point models NeurIPS 2011 Inferring spike-timing-dependent plasticity from spike train data NeurIPS 2011 Learning Attribute-weighted Voter Model over Social Networks ACML 2011 Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities NeurIPS 2011 Model-Based Proprioceptive State Estimation for Spring-Mass Running RSS 2011 Multicore Gibbs Sampling in Dense, Unstructured Graphs AISTATS 2011 Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning NeurIPS 2011 On the Estimation of α-Divergences AISTATS 2011 On the Relation between Realizable and Nonrealizable Cases of the Sequence Prediction Problem JMLR 2011 On Tracking The Partition Function NeurIPS 2011 Optimal Reinforcement Learning for Gaussian Systems NeurIPS 2011 Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees AISTATS 2011 Periodic Finite State Controllers for Efficient POMDP and DEC-POMDP Planning NeurIPS 2011 Quasi-Newton Methods for Markov Chain Monte Carlo NeurIPS 2011