Knowledge & Reasoning

Partially Observed Maximum Entropy Discrimination Markov Networks NeurIPS 2008 Supervised Bipartite Graph Inference NeurIPS 2008 Using Markov Blankets for Causal Structure Learning JMLR 2008 An Analysis of Convex Relaxations for MAP Estimation NeurIPS 2007 Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm JMLR 2007 Gaussian Process Models for Link Analysis and Transfer Learning NeurIPS 2007 Hidden Common Cause Relations in Relational Learning NeurIPS 2007 Integrating Naïve Bayes and FOIL JMLR 2007 Learning and using relational theories NeurIPS 2007 The Noisy-Logical Distribution and its Application to Causal Inference NeurIPS 2007 Theoretical Analysis of Heuristic Search Methods for Online POMDPs NeurIPS 2007 A Linear Non-Gaussian Acyclic Model for Causal Discovery JMLR 2006 Automated Hierarchy Discovery for Planning in Partially Observable Environments NeurIPS 2006 Bayesian Model Scoring in Markov Random Fields NeurIPS 2006 Combining causal and similarity-based reasoning NeurIPS 2006 Inferring Network Structure from Co-Occurrences NeurIPS 2006 Learning annotated hierarchies from relational data NeurIPS 2006 Learning Structural Equation Models for fMRI NeurIPS 2006 Recursive Attribute Factoring NeurIPS 2006 Stochastic Relational Models for Discriminative Link Prediction NeurIPS 2006 Construction of Conceptual Graph Representation of Texts NAACL 2004 Learning Probabilistic Models of Link Structure JMLR 2002