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ORCID17. ILP 2007: Corvallis, Oregon, USA
- Hendrik Blockeel
, Jan Ramon, Jude W. Shavlik, Prasad Tadepalli:
Inductive Logic Programming, 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers. Lecture Notes in Computer Science 4894, Springer 2008, ISBN 978-3-540-78468-5
Invited Talks
- Paolo Frasconi:
Learning with Kernels and Logical Representations. 1-3 - David D. Jensen:
Beyond Prediction: Directions for Probabilistic and Relational Learning. 4-21
Extended Abstracts
- Jianzhong Chen, Stephen H. Muggleton, Jose Santos:
Learning Probabilistic Logic Models from Probabilistic Examples (Extended Abstract). 22-23 - Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel:
Learning Directed Probabilistic Logical Models Using Ordering-Search. 24 - Frédéric Koriche:
Learning to Assign Degrees of Belief in Relational Domains. 25-26 - Jennifer Neville, David D. Jensen:
Bias/Variance Analysis for Relational Domains. 27-28
Full Papers
- Claudia d'Amato, Nicola Fanizzi, Floriana Esposito:
Induction of Optimal Semantic Semi-distances for Clausal Knowledge Bases. 29-38 - Grant Anderson, Bernhard Pfahringer:
Clustering Relational Data Based on Randomized Propositionalization. 39-48 - Nicolas Baskiotis, Michèle Sebag:
Structural Statistical Software Testing with Active Learning in a Graph. 49-62 - Will Bridewell, Ljupco Todorovski:
Learning Declarative Bias. 63-77 - Rui Camacho, Nuno A. Fonseca, Ricardo Rocha, Vítor Santos Costa:
ILP : - Just Trie It. 78-87 - Tom Croonenborghs, Kurt Driessens, Maurice Bruynooghe:
Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning. 88-97 - Aram Galstyan, Paul R. Cohen:
Empirical Comparison of "Hard" and "Soft" Label Propagation for Relational Classification. 98-111 - Romaric Gaudel, Michèle Sebag, Antoine Cornuéjols:
A Phase Transition-Based Perspective on Multiple Instance Kernels. 112-121 - Mark Goadrich, Jude W. Shavlik:
Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates. 122-131 - Evelina Lamma, Paola Mello, Fabrizio Riguzzi, Sergio Storari:
Applying Inductive Logic Programming to Process Mining. 132-146 - Jens Lehmann, Pascal Hitzler:
A Refinement Operator Based Learning Algorithm for the ALC Description Logic. 147-160 - Jens Lehmann, Pascal Hitzler:
Foundations of Refinement Operators for Description Logics. 161-174 - Sriraam Natarajan, Prasad Tadepalli, Alan Fern:
A Relational Hierarchical Model for Decision-Theoretic Assistance. 175-190 - Louis Oliphant, Jude W. Shavlik:
Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming. 191-199 - Aline Paes, Gerson Zaverucha, Vítor Santos Costa:
Revising First-Order Logic Theories from Examples Through Stochastic Local Search. 200-210 - Ganesh Ramakrishnan, Sachindra Joshi, Sreeram Balakrishnan, Ashwin Srinivasan:
Using ILP to Construct Features for Information Extraction from Semi-structured Text. 211-224 - Oliver Ray, Katsumi Inoue:
Mode-Directed Inverse Entailment for Full Clausal Theories. 225-238 - Yosuke Sasaki, Hitoshi Yamasaki, Takayoshi Shoudai, Tomoyuki Uchida:
Mining of Frequent Block Preserving Outerplanar Graph Structured Patterns. 239-253 - Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richard Maclin:
Relational Macros for Transfer in Reinforcement Learning. 254-268 - Anneleen Van Assche, Hendrik Blockeel:
Seeing the Forest Through the Trees. 269-279 - Trevor Walker, Lisa Torrey, Jude W. Shavlik, Richard Maclin:
Building Relational World Models for Reinforcement Learning. 280-291 - Xiaobing Wu:
An Inductive Learning System for XML Documents. 292-306
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