Logic List Mailing Archive

ICGI 2020: Grammatical Inference, Virtual

23-27 Aug 2021

The 15th International Conference on Grammatical Inference
https://icgi2020.lis-lab.fr
August 23-27, 2021
To be held online
Submission deadline: May 25, 2021
Submission via EasyChair: https://easychair.org/conferences/?conf=icgi2020

It is our pleasure to inform you about ICGI 2020/21, the major forum for 
presentation and discussion of original research papers on all aspects of 
grammar learning. ICGI, which has been organized bi-annually since the 
early nineties, will be held on-line in August 2021 after being postponed 
due to COVID-19 last year.

ICGI 2020/21 is the place to present your work on learning formal 
grammars, finite state machines, context-free grammars, Markov models, or 
any models related to language theory, stochastic or otherwise. Both 
theoretical work and experimental analyses are welcomed as submissions. 
This year we especially encourage submissions related to connectionist 
models such as neural networks, since there are tutorials scheduled on 
that topic.

The conference will be spread out over August 23-27, featuring a mix of 
live talks, asynchronous video presentations, tutorials, and an online 
competition. There will be one synchronous event per day plus dedicated 
time for each accepted paper; further details will be announced by email.

Invited Speakers:
Dana Fisman (Ben-Gurion University)
Robert Frank (Yale University)
Guillaume Rabusseau (Université de Montréal)
Gail Weiss (Technion - Israel Institute of Technology)
C. Lee Giles (Pennsylvania State University)

More details can be found on our webpage: https://icgi2020.lis-lab.fr/speakers/

On-line Competition
ICGI 2020/21 is hosting a shared task on morphological inflection. An example of English inflection is the conversion of the lemma ?run? to its present participle, ?running?. To participate in the shared task, you will build a system that can learn to solve inflection problems. More details at  https://aryamccarthy.github.io/icgi2020/

Topics of interest
- Theoretical aspects of grammatical inference: learning paradigms, learnability results, complexity of learning;
- Empirical and theoretical research on query learning, active learning, and other interactive learning paradigms;
- Empirical and theoretical research on methods using or including, but not limited to, spectral learning, state-merging, distributional learning, statistical relational learning, statistical inference and/or Bayesian learning;
- Learning algorithms for language classes inside and outside the Chomsky hierarchy. Learning tree and graph grammars;
- Learning probability distributions over strings, trees or graphs, or transductions thereof;
- Learning with contextualized data: for instance, Grammatical inference from strings or trees paired with semantics representations, or learning by situated agents and robots;
- Experimental and theoretical analysis of different approaches to grammar induction, including artificial neural networks, statistical methods, symbolic methods, information-theoretic approaches, minimum description length, complexity-theoretic approaches, heuristic methods, etc;
- Novel approaches to grammatical inference: induction by DNA computing or quantum computing, evolutionary approaches, new representation spaces, etc;
- Successful applications of grammatical learning to tasks in fields including, but not limited to, natural language processing and computational linguistics, model checking and software verification, bioinformatics, robotic planning and control, and pattern recognition.

Types of Contributions
We welcome three types of papers:
- Formal and/or technical papers describe original solutions (theoretical, methodological or conceptual) in the field of grammatical inference. A technical paper should clearly describe the situation or problem tackled, the relevant state of the art, the position or solution suggested and the benefits of the contribution;
- Position papers can describe completely new research positions or approaches, open problems. Current limits can be discussed. In all cases rigor in presentation will be required. Such papers must describe precisely the situation, problem, or challenge addressed, and demonstrate how current methods, tools, ways of reasoning, may be inadequate;
- Tool papers describing a new tool for grammatical inference. The tool must be publicly available and the paper has to contain several use-case studies describing the use of the tool. In addition, the paper should clearly describe the implemented algorithms, input parameters and syntax, and the produced output.
Selected authors will be encouraged to submit an extended version of their work to an upcoming  special issue of an international journal (to be announced).
Guidelines for authors
Accepted papers will be published within the Proceedings of Machine Learning Research series (http://proceedings.mlr.press/). They must be submitted in pdf format through EasyChair. The total length of the paper should not exceed 12 pages on A4-size paper. The prospective authors are strongly recommended to use the JMLR style file for LaTeX (https://ctan.org/tex-archive/macros/latex/contrib/jmlr) since it will be the required format for the final published version.

Important Dates
Deadline for submissions is: May 25, 2021
Notification of acceptance: July 5, 2021
Camera-ready copy: July 30, 2021
Conference: August 23-27, 2021

Conference Chairs:
Jane Chandlee, Haverford College
Rémi Eyraud, University of Saint-Etienne
Jeffrey Heinz, Stony Brook University
Adam Jardine, Rutgers University
Menno van Zaanen, South African Centre for Digital Language Resources

Program committee consists of almost thirty recognizable researchers 
(names can be found on our website: 
https://icgi2020.lis-lab.fr/committees/).

For any enquiries regarding general issues, the program, or if you are a 
potential sponsor, please contact one of the conference chairs.

We look forward to seeing you at ICGI 2020/21.

Sincerely,
Adam, Jane, Jeffrey, Menno, and Rémi
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