Provisional Program

September 16

13:00–19:00 Registration desk is open during the collocated event:
ELC workshop on Learning Theory and Complexity

September 17

09:30– Registration
10:00–10:05 Opening
10:05–11:05 Invited Talk
Edward Stabler
Towards a rationalist theory of language acquisition (I)
11:05–11:20 Break
11:20–11:55 Yasuhiro Tajima and Genichiro Kikui
An example distribution for probabilistic query learning of simple deterministic languages
11:55–12:30 Menno van Zaanen and Nanne van Noord
Evaluation of generation and selection in context-free grammar learning systems
12:30–14:00 Lunch
14:00–14:35 Chihiro Shibata
Inferring (k,l)-context-sensitive probabilistic context-free grammars using hierarchical Pitman-Yor processes
14:35–15:10 François Coste, Gaëlle Garet and Jacques Nicolas
A bottom-up efficient algorithm learning substitutable languages from positive examples
15:10–15:45 Wojciech Wieczorek and Olgierd Unold
Induction of directed acyclic word graph in a bioinformatics task
15:45–16:00 Break
16:00–16:50 Best Student Prize Talk
James Scicluna and Colin de la Higuera
Grammatical inference of some probabilistic context-free grammars from positive data using minimum satisfiability

September 18

9:30–10:30 Invited Talk
Hiroshi Sakamoto
Grammar Compression: Grammatical Inference by Compression and Its Application to Real Data
10:30–10:45 Break
10:45–11:20 Achilles Beros and Colin de la Higuera
A canonical semi-deterministic transducer
11:20–11:55 Ali Khalili and Armando Tacchella
Learning non-deterministic Mealy machines
11:55–12:30 Adam Jardine, Jane Chandlee, Rémi Eyraud and Jeffrey Heinz
Very efficient learning of structured classes of subsequential functions from positive data
12:30–13:30 Lunch
13:30–18:30 Excursion (Sanjusangen-do, Nijo-jo, Kiyomizu-dera. Subject to change)
19:00–21:00 Banquet

September 19

09:30–10:30 Invited Talk
Edward Stabler
Towards a rationalist theory of language acquisition (II)
10:30–10:45 Break
10:45–11:20 Guillaume Rabusseau and François Denis
Maximizing a tree series in the representation space
11:20–11:55 Mattias Gybels, François Denis and Amaury Habrard
Some improvements of the spectral learning approach for probabilistic grammatical inference
11:55–13:50 Lunch
13:50–14:25 Malte Isberner and Bernhard Steffen
An abstract framework for counterexample analysis in active automata learning
14:25–15:00 Rick Smetsers, Michele Volpato, Frits Vaandrager and Sicco Verwer
Bigger is not always better: on the quality of hypotheses in active automata learning
15:00–15:15 Break
15:15–15:35 Jie Fu, Jeffrey Heinz, Adam Jardine and Herbert G. Tanner
Perception-based Grammatical Inference for Adaptive Systems
15:35–15:55 Keisuke Otaki and Akihiro Yamamoto
Probabilistic Models Based on Regular Pattern Languages and Their Learning Problems
15:55–16:15 Matthias Gallé and Sunil Gandhi
Evaluation of Grammatical Inference Algorithms through Document Classification
16:15–16:30 Break
16:30–17:00 Business Meeting