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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

A Method of Moments for Mixture Models and Hidden Markov Models COLT 2012
PAC-Bayesian Bound for Gaussian Process Regression and Multiple Kernel Additive Model COLT 2012
Learning Latent Variable Models by Pairwise Cluster Comparison ACML 2012
Causality with Gates AISTATS 2012
A Composite Likelihood View for Multi-Label Classification AISTATS 2012
FastEx: Hash Clustering with Exponential Families NIPS 2012
Forward-Backward Activation Algorithm for Hierarchical Hidden Markov Models NIPS 2012
Repulsive Mixtures NIPS 2012
Truly Nonparametric Online Variational Inference for Hierarchical Dirichlet Processes NIPS 2012
Multiresolution Gaussian Processes NIPS 2012
Semiparametric Pseudo-Likelihood Estimation in Markov Random Fields AISTATS 2012
Lightning-speed Structure Learning of Nonlinear Continuous Networks AISTATS 2012
Copula Network Classifiers (CNCs) AISTATS 2012
On Sparse, Spectral and Other Parameterizations of Binary Probabilistic Models AISTATS 2012
Sample Complexity of Composite Likelihood AISTATS 2012
Adaptive Metropolis with Online Relabeling AISTATS 2012
Discriminative Mixtures of Sparse Latent Fields for Risk Management AISTATS 2012
Dynamic Pruning of Factor Graphs for Maximum Marginal Prediction NIPS 2012
Variational Inference for Crowdsourcing NIPS 2012
Spectral learning of linear dynamics from generalised-linear observations with application to neural population data NIPS 2012
Learning Label Trees for Probabilistic Modelling of Implicit Feedback NIPS 2012
Probabilistic Event Cascades for Alzheimer's disease NIPS 2012
Meta-Gaussian Information Bottleneck NIPS 2012
Newton-Like Methods for Sparse Inverse Covariance Estimation NIPS 2012
Transelliptical Graphical Models NIPS 2012