Bayesian & Probabilistic

Inference with Multivariate Heavy-Tails in Linear Models NeurIPS 2010 Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks NeurIPS 2010 Joint Analysis of Time-Evolving Binary Matrices and Associated Documents NeurIPS 2010 Layered image motion with explicit occlusions, temporal consistency, and depth ordering NeurIPS 2010 Learning concept graphs from text with stick-breaking priors NeurIPS 2010 Learning Efficient Markov Networks NeurIPS 2010 Learning invariant features using the Transformed Indian Buffet Process NeurIPS 2010 Learning Non-Stationary Dynamic Bayesian Networks JMLR 2010 Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors NeurIPS 2010 Learning the context of a category NeurIPS 2010 libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models JMLR 2010 Lifted Inference Seen from the Other Side : The Tractable Features NeurIPS 2010 Linear readout from a neural population with partial correlation data NeurIPS 2010 MAP Estimation for Graphical Models by Likelihood Maximization NeurIPS 2010 Matrix-Variate Dirichlet Process Mixture Models AISTATS 2010 Maximum-likelihood learning of cumulative distribution functions on graphs AISTATS 2010 Mixture of time-warped trajectory models for movement decoding NeurIPS 2010 Modeling annotator expertise: Learning when everybody knows a bit of something AISTATS 2010 More data means less inference: A pseudo-max approach to structured learning NeurIPS 2010 Movement extraction by detecting dynamics switches and repetitions NeurIPS 2010 Near-Optimal Bayesian Active Learning with Noisy Observations NeurIPS 2010 Nonparametric Bayesian Matrix Factorization by Power-EP AISTATS 2010 Nonparametric Bayesian Policy Priors for Reinforcement Learning NeurIPS 2010 On Combining Graph-based Variance Reduction schemes AISTATS 2010 Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets NeurIPS 2010