Abstract is missing.
- Learning with Kernels and Logical RepresentationsPaolo Frasconi. 1-3 [doi]
- Beyond Prediction: Directions for Probabilistic and Relational LearningDavid D. Jensen. 4-21 [doi]
- Learning Probabilistic Logic Models from Probabilistic Examples (Extended Abstract)Jianzhong Chen, Stephen Muggleton, Jose Santos. 22-23 [doi]
- Learning Directed Probabilistic Logical Models Using Ordering-SearchDaan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel. 24 [doi]
- Learning to Assign Degrees of Belief in Relational DomainsFrédéric Koriche. 25-26 [doi]
- Bias/Variance Analysis for Relational DomainsJennifer Neville, David Jensen. 27-28 [doi]
- Induction of Optimal Semantic Semi-distances for Clausal Knowledge BasesClaudia d Amato, Nicola Fanizzi, Floriana Esposito. 29-38 [doi]
- Clustering Relational Data Based on Randomized PropositionalizationGrant Anderson, Bernhard Pfahringer. 39-48 [doi]
- Structural Statistical Software Testing with Active Learning in a GraphNicolas Baskiotis, Michèle Sebag. 49-62 [doi]
- Learning Declarative BiasWill Bridewell, Ljupco Todorovski. 63-77 [doi]
- ILP : - Just Trie ItRui Camacho, Nuno A. Fonseca, Ricardo Rocha, Vítor Santos Costa. 78-87 [doi]
- Learning Relational Options for Inductive Transfer in Relational Reinforcement LearningTom Croonenborghs, Kurt Driessens, Maurice Bruynooghe. 88-97 [doi]
- Empirical Comparison of Hard and Soft Label Propagation for Relational ClassificationAram Galstyan, Paul R. Cohen. 98-111 [doi]
- A Phase Transition-Based Perspective on Multiple Instance KernelsRomaric Gaudel, Michèle Sebag, Antoine Cornuéjols. 112-121 [doi]
- Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic EstimatesMark Goadrich, Jude W. Shavlik. 122-131 [doi]
- Applying Inductive Logic Programming to Process MiningEvelina Lamma, Paola Mello, Fabrizio Riguzzi, Sergio Storari. 132-146 [doi]
- A Refinement Operator Based Learning Algorithm for the ::::ALC:::: Description LogicJens Lehmann, Pascal Hitzler. 147-160 [doi]
- Foundations of Refinement Operators for Description LogicsJens Lehmann, Pascal Hitzler. 161-174 [doi]
- A Relational Hierarchical Model for Decision-Theoretic AssistanceSriraam Natarajan, Prasad Tadepalli, Alan Fern. 175-190 [doi]
- Using Bayesian Networks to Direct Stochastic Search in Inductive Logic ProgrammingLouis Oliphant, Jude W. Shavlik. 191-199 [doi]
- Revising First-Order Logic Theories from Examples Through Stochastic Local SearchAline Paes, Gerson Zaverucha, Vítor Santos Costa. 200-210 [doi]
- Using ILP to Construct Features for Information Extraction from Semi-structured TextGanesh Ramakrishnan, Sachindra Joshi, Sreeram Balakrishnan, Ashwin Srinivasan. 211-224 [doi]
- Mode-Directed Inverse Entailment for Full Clausal TheoriesOliver Ray, Katsumi Inoue. 225-238 [doi]
- Mining of Frequent Block Preserving Outerplanar Graph Structured PatternsYosuke Sasaki, Hitoshi Yamasaki, Takayoshi Shoudai, Tomoyuki Uchida. 239-253 [doi]
- Relational Macros for Transfer in Reinforcement LearningLisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin. 254-268 [doi]
- Seeing the Forest Through the TreesAnneleen Van Assche, Hendrik Blockeel. 269-279 [doi]
- Building Relational World Models for Reinforcement LearningTrevor Walker, Lisa Torrey, Jude W. Shavlik, Richard Maclin. 280-291 [doi]
- An Inductive Learning System for XML DocumentsXiaobing Wu. 292-306 [doi]