ML 2013 - Special Issue on Grammatical Inference - Machine Learning Journal

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Category ML 2013

Deadline: December 01, 2012 | Date: June 01, 2013

Venue/Country: Online, Online

Updated: 2012-06-27 07:38:13 (GMT+9)

Call For Papers - CFP

Special Issue on Grammatical

Inference

Machine Learning Journal

http://www.springer.com/computer/ai/journal/10994

Grammatical inference studies the problem of how a grammar can be

reliably and automatically inferred from information about the behavior

of the system the grammar characterizes. Generative grammars are used to

model a range of behaviors in fields such as bioinformatics, psychology,

linguistics, natural language processing, software engineering, and many

other areas.

Research in grammatical inference continually appears in conferences,

including the biennial International Conference of Grammatical Inference

(ICGI), and journals, and is the subject of a recent book (de la Higuera

2010). The purpose of this special issue is to present the best,

cutting-edge research on grammatical inference to the readership of the

Machine Learning Journal.

We invite high quality submissions from researchers in all areas of

grammatical inference, including, but not limited to, the following areas:

* Theoretical aspects of grammatical inference: learning paradigms,

learnability results, complexity of learning. Efficient learning

algorithms for language classes inside and outside the Chomsky

hierarchy. Learning tree and graph grammars. Learning distributions

over strings, trees or graphs.

* Theoretical and experimental 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 inference to tasks in

natural language processing, bioinformatics, machine translation,

pattern recognition, language acquisition, software engineering,

computational linguistics, spam and malware detection, cognitive

psychology, robotics etc.

*Paper Submission*

Authors are encouraged to submit high-quality, original work that has

neither appeared in, nor is under consideration by, other journals.

Springer offers authors, editors and reviewers of Machine Learning a

web-enabled online manuscript submission and review system, giving

authors the ability to track the review process of their manuscript.

Manuscripts should be submitted to: http://MACH.edmgr.com. This online

system offers easy and straightforward log-in and submission procedures,

and supports a wide range of submission file formats. When submitting

please be sure to choose the manuscript type, "Grammatical Inference."

*Important Dates*

. Paper submission deadline: December 1, 2012

. Notification of acceptance: February 1, 2013

. Final manuscript: June 1, 2013

*Guest Editors*

Jeffrey Heinz (University of Delaware, heinzudel.edu)

Colin de la Higuera (University of Nantes, cdlhuniv-nantes.fr)

Tim Oates (University of Maryland, oatescs.umbc.edu)