approximate inference

Perturbation Corrections in Approximate Inference: Mixture Modelling Applications JMLR 2009 Approximations for Binary Gaussian Process Classification JMLR 2008 Improved Moves for Truncated Convex Models NeurIPS 2008 Improving on Expectation Propagation NeurIPS 2008 MAS: a multiplicative approximation scheme for probabilistic inference NeurIPS 2008 Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation NeurIPS 2008 Agreement-Based Learning NeurIPS 2007 An Analysis of Convex Relaxations for MAP Estimation NeurIPS 2007 Discovering Weakly-Interacting Factors in a Complex Stochastic Process NeurIPS 2007 Local Algorithms for Approximate Inference in Minor-Excluded Graphs NeurIPS 2007 Loop Corrections for Approximate Inference on Factor Graphs JMLR 2007 Structured Learning with Approximate Inference NeurIPS 2007 Theoretical Analysis of Heuristic Search Methods for Online POMDPs NeurIPS 2007 TrueSkill Through Time: Revisiting the History of Chess NeurIPS 2007 A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems NeurIPS 2006 Approximate inference using planar graph decomposition NeurIPS 2006 Efficient Structure Learning of Markov Networks using L_1-Regularization NeurIPS 2006 Estimating the “Wrong” Graphical Model: Benefits in the Computation-Limited Setting JMLR 2006 Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems JMLR 2006 Learning Nonparametric Models for Probabilistic Imitation NeurIPS 2006 Assessing Approximate Inference for Binary Gaussian Process Classification JMLR 2005 Expectation Consistent Approximate Inference JMLR 2005 Loopy Belief Propagation: Convergence and Effects of Message Errors JMLR 2005 An Approximate Analytical Approach to Resampling Averages JMLR 2003 PAC-Bayesian Generalisation Error Bounds for Gaussian Process Classification JMLR 2002