27th International Conference on Inductive Logic Programming
4-6 Sep 2017 Orléans (France)

For authors > Accepted papers

ILP 2017 Accepted Papers (regular paper)

Logical Vision: One-Shot Meta-Interpretive Learning from Real Images.
Wang-Zhou Dai, Stephen Muggleton, Jing Wen, Alireza Tamaddoni-Nezhad and Zhi-Hua Zhou.

Demystifying Relational Latent Representations.
Sebastijan Dumancic and Hendrik Blockeel.

Distributed Online Learning of Event Definitions.
Nikos Katzouris, Alexander Artikis and Georgios Paliouras.

Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach.
Navdeep Kaur, Gautam Kunapuli, Tushar Khot, Kristian Kersting, William Cohen and Sriraam Natarajan.

Lifted Discriminative Learning of Probabilistic Logic Programs.
Arnaud Nguembang Fadja and Fabrizio Riguzzi.

Learning Programs with Continuous Domains from State Transitions.
Tony Ribeiro, Sophie Tourret, Maxime Folschette, Morgan Magnin, Domenico Borzacchiello, Francisco Chinesta, Olivier Roux and Katsumi Inoue.

Mining rare sequential patterns with ASP
Ahmed Samet, Thomas Guyet and Benjamin Negrevergne.

Stacked Structure Learning for Lifted Relational Neural Networks.
Gustav Šourek, Martin Svatoš, Filip Železný, Steven Schockaert and Ondřej Kuželka.

Mode-Directed Neural-Symbolic Modelling.
Ashwin Srinivasan, Lovekesh Vig and Gautam Shroff.

Pruning Hypothesis Spaces Using Learned Domain Theories.
Martin Svatoš, Gustav Šourek, Filip Zelezny, Steven Schockaert and Ondřej Kuželka.

ILP 2017 Accepted Papers (late-breaking paper)

Relational affordance learning for task-dependent robot grasping.
Laura Antanas, Anton Dries, Plinio Moreno and Luc De Raedt.

A First-Order Axiomatization for Transition Learning with Rich Constraints.
Jachym Barvinek and Filip Zelezny.

Positive and Unlabeled Relational Classification through Label Frequency Estimation.
Jessa Bekker and Jesse Davis.

PU-learning disjunctive concepts in ILP.
Hendrik Blockeel.

Clustering multi-relationnal TV data by diverting supervised ILP.
Vincent Claveau.

The Effect of Predicate Order on Curriculum Learning in ILP.
Hank Conn and Stephen Muggleton.

Probabilistic Logic Models and Their Application to Breast Cancer.
Joana Côrte-Real, Inês Dutra and Ricardo Rocha.

Adaptive Incremental Learning for Statistical Relational Models Using Gradient-Based Boosting.
Yulong Gu and Paolo Missier.

Parallel ILP System for Super Linear Speed up.
Hiroyuki Nishiyama and Hayato Ohwada.

Learning from Ordinal Data with Inductive Logic Programming in Description Logic.
Nunung Nurul Qomariyah and Dimitar Kazakov.

Learning Logic Program Representation for Delayed Systems with Limited Training Data.
Yin Jun Phua, Tony Ribeiro, Sophie Tourret and Katsumi Inoue.

Mining Tree Patterns with Partially Injective Homomorphisms.
Till Hendrik Schulz, Tamás Horváth, Pascal Welke and Stefan Wrobel.

Learning of Primitive Formal Systems Defining Labeled Ordered Tree Languages via Queries.
Tomoyuki Uchida, Satoshi Matsumoto, Takayoshi Shoudai, Yusuke Suzuki and Tetsuhiro Miyahara.

Embeddings Considered Unhelpful?
Lovekesh Vig, Ashwin Srinivasan, Michael Bain and Ankit Verma.


ILP 2017 Accepted Papers (already published paper)

Solving Probability Problems in Natural Language.
Anton Dries, Angelika Kimmig, Jesse Davis, Vaishak Belle and Luc De Raedt.

Clustering-Based Relational Unsupervised Representation Learning with an Explicit Distributed Representation
Sebastijan Dumancic and Hendrik Blockeel.

Learning Commonalities in RDF
Sara El Hassad, Francois Goasdoue and Helene Jaudoin.

A collective, probabilistic approach to schema mapping.
Angelika Kimmig, Alex Memory, Renee Miller and Lise Getoor.

Towards Automatically Setting Language Bias in Relational Learning.
Jose Picado, Arash Termehchy, Alan Fern and Sudhanshu Pathak.

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