Bayesian & Probabilistic

Learning Chordal Markov Networks by Constraint Satisfaction NeurIPS 2013 Learning CRFs for Image Parsing with Adaptive Subgradient Descent ICCV 2013 Learning Efficient Random Maximum A-Posteriori Predictors with Non-Decomposable Loss Functions NeurIPS 2013 Learning Feature Selection Dependencies in Multi-task Learning NeurIPS 2013 Learning Gaussian Graphical Models with Observed or Latent FVSs NeurIPS 2013 Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition NeurIPS 2013 Learning Linear Bayesian Networks with Latent Variables ICML 2013 Learning Multiple Behaviors from Unlabeled Demonstrations in a Latent Controller Space ICML 2013 Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes AISTATS 2013 Learning Stochastic Inverses NeurIPS 2013 Learning the beta-Divergence in Tweedie Compound Poisson Matrix Factorization Models ICML 2013 Learning the Local Statistics of Optical Flow NeurIPS 2013 Learning the Structure of Sum-Product Networks ICML 2013 Learning to Pass Expectation Propagation Messages NeurIPS 2013 Lexical and Hierarchical Topic Regression NeurIPS 2013 Linear Approximation to ADMM for MAP inference ACML 2013 Locally Adaptive Bayesian Multivariate Time Series NeurIPS 2013 Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization CVPR 2013 Machine Teaching for Bayesian Learners in the Exponential Family NeurIPS 2013 Marginals-to-Models Reducibility NeurIPS 2013 Markov Network-Based Unified Classifier for Face Identification ICCV 2013 Matrix Completion From any Given Set of Observations NeurIPS 2013 Memoized Online Variational Inference for Dirichlet Process Mixture Models NeurIPS 2013 Message Passing Inference with Chemical Reaction Networks NeurIPS 2013 Message passing with l1 penalized KL minimization ICML 2013