Artificial Intelligence

Learning Hidden Variable Networks: The Information Bottleneck Approach JMLR 2005 Learning Module Networks JMLR 2005 Learning Multiple Tasks with Kernel Methods JMLR 2005 Local Propagation in Conditional Gaussian Bayesian Networks JMLR 2005 Loopy Belief Propagation: Convergence and Effects of Message Errors JMLR 2005 Probabilistic Non-linear Principal Component Analysis with Gaussian Process Latent Variable Models JMLR 2005 Square Root SAM RSS 2005 Time Complexity of Sensor-Based Vehicle Routing RSS 2005 What's Strange About Recent Events (WSARE): An Algorithm for the Early Detection of Disease Outbreaks JMLR 2005 Exact Bayesian Structure Discovery in Bayesian Networks JMLR 2004 Hierarchical Latent Class Models for Cluster Analysis JMLR 2004 Large-Sample Learning of Bayesian Networks is NP-Hard JMLR 2004 Probability Product Kernels JMLR 2004 An Empirical Study of the Use of Relevance Information in Inductive Logic Programming JMLR 2003 Blind Source Recovery: A Framework in the State Space JMLR 2003 Combining Knowledge from Different Sources in Causal Probabilistic Models JMLR 2003 Energy-Based Models for Sparse Overcomplete Representations JMLR 2003 Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains JMLR 2003 ILP: A Short Look Back and a Longer Look Forward JMLR 2003 Learning Behavior-Selection by Emotions and Cognition in a Multi-Goal Robot Task JMLR 2003 Learning Probabilistic Models: An Expected Utility Maximization Approach JMLR 2003 Matching Words and Pictures JMLR 2003 Nash Q-Learning for General-Sum Stochastic Games JMLR 2003 On Inclusion-Driven Learning of Bayesian Networks JMLR 2003 Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet JMLR 2003