Bayesian & Probabilistic

The Coloured Noise Expansion and Parameter Estimation of Diffusion Processes NeurIPS 2012 The Optimality of Jeffreys Prior for Online Density Estimation and the Asymptotic Normality of Maximum Likelihood Estimators COLT 2012 The Time-Marginalized Coalescent Prior for Hierarchical Clustering NeurIPS 2012 The variational hierarchical EM algorithm for clustering hidden Markov models NeurIPS 2012 Topic-Partitioned Multinetwork Embeddings NeurIPS 2012 Training sparse natural image models with a fast Gibbs sampler of an extended state space NeurIPS 2012 Transelliptical Graphical Models NeurIPS 2012 Truly Nonparametric Online Variational Inference for Hierarchical Dirichlet Processes NeurIPS 2012 Truncation-free Online Variational Inference for Bayesian Nonparametric Models NeurIPS 2012 Variable Selection for Gaussian Graphical Models AISTATS 2012 Variational Bayesian Matching ACML 2012 Variational Inference for Crowdsourcing NeurIPS 2012 Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding NeurIPS 2012 Accelerated Adaptive Markov Chain for Partition Function Computation NeurIPS 2011 A concave regularization technique for sparse mixture models NeurIPS 2011 Active learning of neural response functions with Gaussian processes NeurIPS 2011 Additive Gaussian Processes NeurIPS 2011 A Dynamic Relational Infinite Feature Model for Longitudinal Social Networks AISTATS 2011 A Global Structural EM Algorithm for a Model of Cancer Progression NeurIPS 2011 Algorithms for Hyper-Parameter Optimization NeurIPS 2011 A Model for Temporal Dependencies in Event Streams NeurIPS 2011 Analytical Results for the Error in Filtering of Gaussian Processes NeurIPS 2011 An Application of Tree-Structured Expectation Propagation for Channel Decoding NeurIPS 2011 Anatomically Constrained Decoding of Finger Flexion from Electrocorticographic Signals NeurIPS 2011 An ideal observer model for identifying the reference frame of objects NeurIPS 2011