20. ILP 2010: Florence, Italy

Abstracts of Invited Talks

• Michael Kifer:
  Rule Interchange Format: Logic Programming's Second Wind? 1
  
• Avi Pfeffer:
  Practical Probabilistic Programming. 2-3
  
• David Poole:
  Probabilistic Relational Learning and Inductive Logic Programming at a Global Scale. 4-5
  

Research Papers

• Tarek Abudawood, Peter A. Flach:
  Learning Multi-class Theories in ILP. 6-13
  
• Érick Alphonse, Tobias Girschick, Fabian Buchwald, Stefan Kramer:
  A Numerical Refinement Operator Based on Multi-Instance Learning. 14-21
  
• Laura Antanas, Martijn van Otterlo, José Oramas M., Tinne Tuytelaars, Luc De Raedt:
  Not Far Away from Home: A Relational Distance-Based Approach to Understanding Images of Houses. 22-29
  
• Stefano Bragaglia, Fabrizio Riguzzi:
  Approximate Inference for Logic Programs with Annotated Disjunctions. 30-37
  
• James Cussens:
  Approximate Bayesian Computation for the Parameters of PRISM Programs. 38-46
  
• Luc De Raedt, Ingo Thon:
  Probabilistic Rule Learning. 47-58
  
• Nuno A. Fonseca, Max Pereira, Vítor Santos Costa, Rui Camacho:
  Interactive Discriminative Mining of Chemical Fragments. 59-66
  
• Beatriz García Jiménez, Agapito Ledezma, Araceli Sanchís:
  MMRF for Proteome Annotation Applied to Human Protein Disease Prediction. 67-75
  
• Bernd Gutmann, Manfred Jaeger, Luc De Raedt:
  Extending ProbLog with Continuous Distributions. 76-91
  
• Yi Huang, Volker Tresp, Markus Bundschus, Achim Rettinger, Hans-Peter Kriegel:
  Multivariate Prediction for Learning on the Semantic Web. 92-104
  
• Alberto Illobre, Jorge Gonzalez, Ramón P. Otero, Jose Santos:
  Learning Action Descriptions of Opponent Behaviour in the Robocup 2D Simulation Environment. 105-113
  
• Katsumi Inoue, Andrei Doncescu, Hidetomo Nabeshima:
  Hypothesizing about Causal Networks with Positive and Negative Effects by Meta-level Abduction. 114-129
  
• Srihari Kalgi, Chirag Gosar, Prasad Gawde, Ganesh Ramakrishnan, Kekin Gada, Chander Iyer, T. V. S. Kiran, Ashwin Srinivasan:
  BET : An Inductive Logic Programming Workbench. 130-137
  
• Ondrej Kuzelka, Filip Zelezný:
  Seeing the World through Homomorphism: An Experimental Study on Reducibility of Examples. 138-145
  
• Matthieu Lopez, Lionel Martin, Christel Vrain:
  Learning Discriminant Rules as a Minimal Saturation Search. 146-157
  
• Stephen Muggleton, Jianzhong Chen, Hiroaki Watanabe, Stuart J. Dunbar, Charles Baxter, Richard Currie, José Domingo Salazar, Jan Taubert, Michael J. E. Sternberg:
  Variation of Background Knowledge in an Industrial Application of ILP. 158-170
  
• Naveen Nair, Anandraj Govindan, Chander Jayaraman, T. V. S. Kiran, Ganesh Ramakrishnan:
  Pruning Search Space for Weighted First Order Horn Clause Satisfiability. 171-180
  
• Yusuke Nakano, Nobuhiro Inuzuka:
  Multi-relational Pattern Mining Based-on Combination of Properties with Preserving Their Structure in Examples. 181-189
  
• Andrej Oblak, Ivan Bratko:
  Learning from Noisy Data Using a Non-covering ILP Algorithm. 190-197
  
• Niels Pahlavi, Stephen Muggleton:
  Can HOLL Outperform FOLL? 198-205
  
• Christophe Rodrigues, Pierre Gérard, Céline Rouveirol:
  Incremental Learning of Relational Action Models in Noisy Environments. 206-213
  
• Jose Santos, Stephen Muggleton:
  When Does It Pay Off to Use Sophisticated Entailment Engines in ILP? 214-221
  
• Alireza Tamaddoni-Nezhad, Stephen Muggleton:
  Stochastic Refinement. 222-237
  
• David Vaz, Vítor Santos Costa, Michel Ferreira:
  Fire! Firing Inductive Rules from Economic Geography for Fire Risk Detection. 238-252
  
• Trevor Walker, Ciaran O'Reilly, Gautam Kunapuli, Sriraam Natarajan, Richard Maclin, David Page, Jude W. Shavlik:
  Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge. 253-268
  
• Radomír Cernoch, Filip Zelezný:
  Speeding Up Planning through Minimal Generalizations of Partially Ordered Plans. 269-276
  

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