Logic List Mailing Archive

LearnAut: Learning & Automata

19 Jun 2017
Reykjavik, Iceland

Call for Papers: Learning and Automata (LearnAut) -- LICS 2017 Workshop

June 19, Reykjavik (Iceland)

Submission deadline: April 1st (only 10 days left!)

Website: https://learnaut.wordpress.com/


Grammatical Inference (GI) studies machine learning algorithms for 
classical recursive models of computations like automata and grammars. The 
expressive power of these models and the complexity of associated 
computational problems are a major research topic within theoretical 
computer science (TCS). This workshop aims at offering a favorable place 
for dialogue and at generating discussions between researchers from these 
two communities.


The workshop will have a particular emphasis on the recent successes due 
to collaborations between members with these two different backgrounds.


We invite submissions of recent works, possibly preliminary ones, related 
to the theme of the workshop. Similarly to how main machine learning 
conferences and workshops are organized, all accepted abstracts will be 
part of a poster session held during the workshop. Additionally, 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.

Topics of interest include (but are not limited to):

- 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.

- Relations between automata and recurrent neural networks.

- 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.

- Logical aspects of learning and grammatical inference.

- Theoretical studies of learnable classes of languages/representations.

- Metrics and other error measures between automata or formal languages.


The workshop will not have formal proceedings, but authors of accepted 
abstracts can choose to have their work published on the workshop webpage. 
Depending on the success of LearnAut, a special issue in a computer 
science journal may be edited, to which participants will be strongly 
encouraged to submit.


** Invited speakers **


Kim G. Larsen (Aalborg)

Mehryar Mohri (NYU & Google)

Alexandra Silva (UCL) [TBC]


** Submission instructions **


Submissions in the form of extended abstracts must be at most 4 pages long 
(plus at most two for bibliography and possible appendixes) and adhere to 
the IEEE Proceedings 2-column 10pt format used by LICS; LaTeX style files 
are available at 
http://www.ctan.org/tex-archive/macros/latex/contrib/IEEEtran/. We do 
accept submissions of work recently published or currently under review. 
Submissions do not need to be anonymized.


  - Submission 
url:<https://easychair.org/conferences/?conf=pmpml16>https://easychair.org/conferences/?conf=learnaut2017

  - Submission deadline: April, 1st, 2017

  - Notification of acceptance: mid-April, 2017

  - LICS early registration deadline: 7 April 2017

  - workshop LICS early registration deadline:5 May 2017


** Program Committee **


Dana Angluin (Yale)

Jorge Castro (UPC)

François Denis (Aix-Marseille)

Jeff Heinz (Delaware)

Colin de la Higuera (Nantes)

Falk Howar (TU Clausthal)

José Oncina (Alicante)

Prakash Panangaden (McGill)

Ariadna Quattoni (Xerox)

Bernhard Steffen (TU Dortmund)

Sicco Verwer (TU Delft)

James Worrell (Oxford)


** Organizers **


Borja Balle (Lancaster)

Leonor Becerra-Bonache (Jean Monnet)

Remi Eyraud (Aix-Marseille)

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