LearnAut 2024: Learning and Automata 2024 Tallin, Estonia, July 7, 2024 |
Conference website | https://learnaut24.github.io/ |
Submission link | https://easychair.org/conferences/?conf=learnaut2024 |
Submission deadline | April 25, 2024 |
Grammatical Inference (GI) studies machine learning algorithms for various language related models such as automata and grammars. Historically, these models are used, for instance, to understand natural language and to do computational linguistics. At the same time, these kind of models are also a major research topic within the ICALP community. These models are central in understanding recursive computations and their expressive power and complexity. In recent years we have seen some important results starting to bridge the gap between both worlds, including applications of learning to formal verification and model checking, (co-)algebraic formulations of automata and grammar learning algorithms and theoretical foundations of learning. The aim of this workshop is to bring together experts on language theory that could benefit from grammatical inference tools, and researchers in grammatical inference who could find new insights for their methods in theoretical computer science.
The aim of this workshop is to bring together experts on language theory that could benefit from grammatical inference tools, and researchers in grammatical inference who could find new insights for their methods in theoretical computer science.
Submission Guidelines
We invite submissions of recent work, including preliminary research, related to the theme of the workshop. The Program Committee will select a subset of the abstracts for oral presentation. At least one author of each accepted abstract is expected to represent it at the workshop.
Note that accepted papers will be made available on the workshop website but will not be part of formal proceedings (i.e., LearnAut is a non-archival workshop).
List of Topics
- Computational complexity of learning problems involving automata and formal languages.
- Algorithms and frameworks for learning models representing language classes inside and outside the Chomsky hierarchy, including tree and graph grammars.
- Learning problems involving models with additional structure, including numeric weights, inputs/outputs such as transducers, register automata, timed automata, Markov reward and decision processes, and semi-hidden Markov models.
- Logical and relational aspects of learning and grammatical inference.
- Theoretical studies of learnable classes of languages/representations.
- Relations between automata or any other models from language theory and deep learning models for sequential data.
- Active learning of finite state machines and formal languages.
- Methods for estimating probability distributions over strings, trees, graphs, or any data used as input for symbolic models.
- Applications of learning to formal verification and (statistical) model checking.
- Metrics and other error measures between automata or formal languages.
Invited Speakers
- Bernhard Aichernig (TU Graz)
- Ryan Cotterell (ETH Zürich)
Committees
Program Committee
- Dana Angluin (Yale University, United States)
- Johanna Björklund (Umeå University, Sweden)
- Benedikt Bollig (LSV, ENS Cachan, CNRS, France)
- Tiago Ferreira (University College London, United Kingdom)
- Jeffrey Heinz (Stony Brook University)
- Colin de la Higuera (Université de Nantes, France)
- Falk Howar (TU Dortmund, Germany)
- Mohammad Mousavi (King’s College London)
- Andrea Pferscher (University of Oslo, Norway)
- Guillaume Rabusseau (McGill University)
- Jurriaan Rot (Radboud University Nijmegen, the Netherlands)
- Ariadna Quattoni (Universitat Politècnica de Catalunya, Spain)
- Sergio Yovine (Universidad ORT, Uruguay)
Organizing committee
- Sophie Fortz (King's College London, UK)
- Franz Mayr (Universidad ORT Uruguay, UY)
- Joshua Moerman (Open Universiteit, Heerlen, NL)
- Matteo Sammartino (Royal Holloway, University of London)
Venue
The fifth edition of "Learning and Automata" (LearnAut) will be held at ICALP/LiCS/FSCD 2024 in Tallinn (Estonia), 7th of July 2024.