Bayesian & Probabilistic

Semi-Supervised Multitask Learning NeurIPS 2007 Simulated Annealing: Rigorous finite-time guarantees for optimization on continuous domains NeurIPS 2007 Sparse Overcomplete Latent Variable Decomposition of Counts Data NeurIPS 2007 Spatial Latent Dirichlet Allocation NeurIPS 2007 Supervised Topic Models NeurIPS 2007 The Generalized FITC Approximation NeurIPS 2007 The Infinite Gamma-Poisson Feature Model NeurIPS 2007 The Infinite Markov Model NeurIPS 2007 The Noisy-Logical Distribution and its Application to Causal Inference NeurIPS 2007 The rat as particle filter NeurIPS 2007 TrueSkill Through Time: Revisiting the History of Chess NeurIPS 2007 Unsupervised Feature Selection for Accurate Recommendation of High-Dimensional Image Data NeurIPS 2007 Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes NeurIPS 2007 Variational Inference for Diffusion Processes NeurIPS 2007 Variational inference for Markov jump processes NeurIPS 2007 A Bayesian Approach to Diffusion Models of Decision-Making and Response Time NeurIPS 2006 Accelerated Variational Dirichlet Process Mixtures NeurIPS 2006 A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation NeurIPS 2006 Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models NeurIPS 2006 A Linear Non-Gaussian Acyclic Model for Causal Discovery JMLR 2006 Analysis of Contour Motions NeurIPS 2006 An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments NeurIPS 2006 A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments NeurIPS 2006 A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems NeurIPS 2006 A PAC-Bayes Risk Bound for General Loss Functions NeurIPS 2006