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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

Spectral Methods Meet EM: A Provably Optimal Algorithm for Crowdsourcing JMLR 2016
Exact Inference on Gaussian Graphical Models of Arbitrary Topology using Path-Sums JMLR 2016
Probabilistic Low-Rank Matrix Completion from Quantized Measurements JMLR 2016
Kernel Mean Shrinkage Estimators JMLR 2016
Copula Ordinal Regression for Joint Estimation of Facial Action Unit Intensity CVPR 2016
Inference Networks for Sequential Monte Carlo in Graphical Models ICML 2016
Stochastic Discrete Clenshaw-Curtis Quadrature ICML 2016
Bayesian Poisson Tucker Decomposition for Learning the Structure of International Relations ICML 2016
Interacting Particle Markov Chain Monte Carlo ICML 2016
Learning and Inference via Maximum Inner Product Search ICML 2016
Conditional Bernoulli Mixtures for Multi-label Classification ICML 2016
Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies ICML 2016
Generalized Direct Change Estimation in Ising Model Structure ICML 2016
On collapsed representation of hierarchical Completely Random Measures ICML 2016
Beyond CCA: Moment Matching for Multi-View Models ICML 2016
Structure Learning of Partitioned Markov Networks ICML 2016
Variable Elimination in the Fourier Domain ICML 2016
Dealbreaker: A Nonlinear Latent Variable Model for Educational Data ICML 2016
Hawkes Processes with Stochastic Excitations ICML 2016
Regime Aware Learning PGM 2016
Bayesian Matrix Factorization with Non-Random Missing Data using Informative Gaussian Process Priors and Soft Evidences PGM 2016
Reintroducing Credal Networks under Epistemic Irrelevance PGM 2016
Statistical Matching of Discrete Data by Bayesian Networks PGM 2016
An Exact Approach to Learning Probabilistic Relational Model PGM 2016
Hybrid Copula Bayesian Networks PGM 2016