Bayesian & Probabilistic

Learning Latent Variable Models by Pairwise Cluster Comparison ACML 2012 Learning Mixtures of Tree Graphical Models NeurIPS 2012 Learning Probability Measures with respect to Optimal Transport Metrics NeurIPS 2012 Learning to Discover Social Circles in Ego Networks NeurIPS 2012 Learning with Target Prior NeurIPS 2012 Lifted Linear Programming AISTATS 2012 Lifted Variable Elimination with Arbitrary Constraints AISTATS 2012 Lightning-speed Structure Learning of Nonlinear Continuous Networks AISTATS 2012 Low rank continuous-space graphical models AISTATS 2012 Majorization for CRFs and Latent Likelihoods NeurIPS 2012 MAP Inference in Chains using Column Generation NeurIPS 2012 Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data AISTATS 2012 MCMC for continuous-time discrete-state systems NeurIPS 2012 Meta-Gaussian Information Bottleneck NeurIPS 2012 Minimization of Continuous Bethe Approximations: A Positive Variation NeurIPS 2012 Mixing Properties of Conditional Markov Chains with Unbounded Feature Functions NeurIPS 2012 Modelling Reciprocating Relationships with Hawkes Processes NeurIPS 2012 Monte Carlo Methods for Maximum Margin Supervised Topic Models NeurIPS 2012 Multilabel Classification using Bayesian Compressed Sensing NeurIPS 2012 Multiplicative Forests for Continuous-Time Processes NeurIPS 2012 Multiresolution Gaussian Processes NeurIPS 2012 Multiresolution Mixture Modeling using Merging of Mixture Components ACML 2012 Natural Images, Gaussian Mixtures and Dead Leaves NeurIPS 2012 Near-Optimal MAP Inference for Determinantal Point Processes NeurIPS 2012 Newton-Like Methods for Sparse Inverse Covariance Estimation NeurIPS 2012