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ORCID27th ILP 2017: Orléans, France
- Nicolas Lachiche, Christel Vrain:
Inductive Logic Programming - 27th International Conference, ILP 2017, Orléans, France, September 4-6, 2017, Revised Selected Papers. Lecture Notes in Computer Science 10759, Springer 2018, ISBN 978-3-319-78089-4 - Laura Antanas, Anton Dries
, Plinio Moreno, Luc De Raedt:
Relational Affordance Learning for Task-Dependent Robot Grasping. 1-15 - Jessa Bekker, Jesse Davis:
Positive and Unlabeled Relational Classification Through Label Frequency Estimation. 16-30 - Joana Côrte-Real, Inês Dutra, Ricardo Rocha:
On Applying Probabilistic Logic Programming to Breast Cancer Data. 31-45 - Wang-Zhou Dai, Stephen H. Muggleton, Jing Wen, Alireza Tamaddoni-Nezhad, Zhi-Hua Zhou:
Logical Vision: One-Shot Meta-Interpretive Learning from Real Images. 46-62 - Sebastijan Dumancic, Hendrik Blockeel:
Demystifying Relational Latent Representations. 63-77 - Nikos Katzouris, Alexander Artikis, Georgios Paliouras:
Parallel Online Learning of Event Definitions. 78-93 - Navdeep Kaur, Gautam Kunapuli, Tushar Khot, Kristian Kersting, William Cohen, Sriraam Natarajan:
Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach. 94-111 - Hiroyuki Nishiyama, Hayato Ohwada:
Parallel Inductive Logic Programming System for Superlinear Speedup. 112-123 - Tony Ribeiro, Sophie Tourret, Maxime Folschette, Morgan Magnin, Domenico Borzacchiello, Francisco Chinesta, Olivier F. Roux, Katsumi Inoue:
Inductive Learning from State Transitions over Continuous Domains. 124-139 - Gustav Sourek, Martin Svatos, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Stacked Structure Learning for Lifted Relational Neural Networks. 140-151 - Martin Svatos, Gustav Sourek, Filip Zelezný, Steven Schockaert, Ondrej Kuzelka:
Pruning Hypothesis Spaces Using Learned Domain Theories. 152-168 - Lovekesh Vig, Ashwin Srinivasan, Michael Bain, Ankit Verma:
An Investigation into the Role of Domain-Knowledge on the Use of Embeddings. 169-183
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