Graphical Models

Modeling homophily and stochastic equivalence in symmetric relational data NeurIPS 2007 Modeling image patches with a directed hierarchy of Markov random fields NeurIPS 2007 Modelling motion primitives and their timing in biologically executed movements NeurIPS 2007 New Outer Bounds on the Marginal Polytope NeurIPS 2007 Rapid Inference on a Novel AND/OR graph for Object Detection, Segmentation and Parsing NeurIPS 2007 Relational Dependency Networks JMLR 2007 Scene Segmentation with CRFs Learned from Partially Labeled Images NeurIPS 2007 Analysis of Contour Motions NeurIPS 2006 Approximate inference using planar graph decomposition NeurIPS 2006 A Probabilistic Algorithm Integrating Source Localization and Noise Suppression of MEG and EEG data NeurIPS 2006 A Robust Procedure For Gaussian Graphical Model Search From Microarray Data With p Larger Than n JMLR 2006 A Small World Threshold for Economic Network Formation NeurIPS 2006 Balanced Graph Matching NeurIPS 2006 Bayesian Model Scoring in Markov Random Fields NeurIPS 2006 Comparative Gene Prediction using Conditional Random Fields 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 Fast Computation of Graph Kernels NeurIPS 2006 Fundamental Limitations of Spectral Clustering NeurIPS 2006 High-Dimensional Graphical Model Selection Using ℓ_1-Regularized Logistic Regression NeurIPS 2006 Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms NeurIPS 2006 Inferring Network Structure from Co-Occurrences NeurIPS 2006 Isotonic Conditional Random Fields and Local Sentiment Flow NeurIPS 2006 Learning Factor Graphs in Polynomial Time and Sample Complexity JMLR 2006 Learning Nonparametric Models for Probabilistic Imitation NeurIPS 2006