Probabilistic Modeling

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 Variable Selection for Gaussian Graphical Models AISTATS 2012 Variational Inference for Crowdsourcing NeurIPS 2012 Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding NeurIPS 2012 A concave regularization technique for sparse mixture models NeurIPS 2011 A Global Structural EM Algorithm for a Model of Cancer Progression NeurIPS 2011 A Model for Temporal Dependencies in Event Streams NeurIPS 2011 Anatomically Constrained Decoding of Finger Flexion from Electrocorticographic Signals NeurIPS 2011 An Unsupervised Decontamination Procedure For Improving The Reliability Of Human Judgments NeurIPS 2011 Approximate inference for the loss-calibrated Bayesian AISTATS 2011 Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints NeurIPS 2011 Bayesian Spike-Triggered Covariance Analysis NeurIPS 2011 Collaborative Filtering with the Trace Norm: Learning, Bounding, and Transducing COLT 2011 Collective Graphical Models NeurIPS 2011 Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs NeurIPS 2011 Complexity of Inference in Latent Dirichlet Allocation NeurIPS 2011 Confidence Sets for Network Structure NeurIPS 2011 Convergent Decomposition Solvers for Tree-reweighted Free Energies AISTATS 2011 Demixed Principal Component Analysis NeurIPS 2011 Dynamical segmentation of single trials from population neural data NeurIPS 2011 Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials NeurIPS 2011 Efficient inference in matrix-variate Gaussian models with \iid observation noise NeurIPS 2011 Empirical models of spiking in neural populations NeurIPS 2011