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Graphical Models

933 directly classified papers

Papers per year

Papers

Relational Dependency Networks JMLR 2007
Walk-Sums and Belief Propagation in Gaussian Graphical Models JMLR 2006
Learning Structural Equation Models for fMRI NIPS 2006
Learning on Graph with Laplacian Regularization NIPS 2006
A Robust Procedure For Gaussian Graphical Model Search From Microarray Data With p Larger Than n JMLR 2006
Bayesian Model Scoring in Markov Random Fields NIPS 2006
Isotonic Conditional Random Fields and Local Sentiment Flow NIPS 2006
Comparative Gene Prediction using Conditional Random Fields NIPS 2006
Stochastic Relational Models for Discriminative Link Prediction NIPS 2006
High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression NIPS 2006
Using Combinatorial Optimization within Max-Product Belief Propagation NIPS 2006
Analysis of Contour Motions NIPS 2006
Approximate inference using planar graph decomposition NIPS 2006
Manifold Denoising NIPS 2006
Structured Prediction, Dual Extragradient and Bregman Projections JMLR 2006
Balanced Graph Matching NIPS 2006
Temporal and Cross-Subject Probabilistic Models for fMRI Prediction Tasks NIPS 2006
Learning Factor Graphs in Polynomial Time and Sample Complexity JMLR 2006
Estimating the “Wrong” Graphical Model: Benefits in the Computation-Limited Setting JMLR 2006
Linear Programming Relaxations and Belief Propagation -- An Empirical Study JMLR 2006
Training Conditional Random Fields for Maximum Labelwise Accuracy NIPS 2006
A Small World Threshold for Economic Network Formation NIPS 2006
Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields NIPS 2006
Hyperparameter Learning for Graph Based Semi-supervised Learning Algorithms NIPS 2006
Linear State-Space Models for Blind Source Separation JMLR 2006