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Category:   E-CFP
Subject:   ICML-2007 Workshop on Challenges and Applications of Grammar Induction
From:   Menno van Zaanen
Email:   menno_(on)_ics.mq.edu.au
Date received:   29 Mar 2007
Deadline:   07 May 2007
Start date:   20 Jun 2007

Please accept our apologies for cross-posting ----------------------------------------------------------------------- Call for participation ICML-2007 Workshop on Challenges and Applications of Grammar Induction In conjunction with the International Conference on Machine Learning, Oregon State University, June 20 - June 24, 2007 ----------------------------------------------------------------------- Description Grammar Induction (GI), also known as Grammatical Inference, is about learning grammars from data. A well-known important application of GI is natural language learning, but it is applicable in a much broader sense to the problem of learning structural models from data. The data typically consists of sequences of discrete events from various domains (such as text, DNA fragments, primary structure of proteins, sequential process log-files and musical scores), but can also include trees and arbitrary graphs (such as metabolic networks and social networks). Typical models include formal grammars (regular, context-free, context- sensitive, . . .), and statistical models in related formalisms such as probabilistic automata, hidden Markov models, probabilistic transducers or conditional random fields. The CAGI workshop aims at highlighting current challenges in grammar induction with a special focus on applicability issues including: - practical evaluations demonstrating the usefulness of the proposed techniques, - novel applications of grammar induction algorithms, - noise resistant approaches, - semi-supervised grammar learning, - learning from partial sequences or streams, - approximate induction and model optimization, - experimental assessments illustrating the current limit(s) of the GI field, - practical complexity and scalability issues (alphabet size, noise level, data sparseness, data inconsistency, . . .), - evaluation of similarity learning algorithms from structured data (pair-HMM learning, stochastic transducer learning, . . .). Workshop Format The workshop will include presentations of peer-reviewed papers. Each such paper will be assigned 30 minutes, including 10 minutes for discussion. Each half-day will start with an invited paper for 45 minutes including the discussion. The day will be concluded with an open panel for discussing the key lessons learned and pointing at relevant research perspectives. Submission Information Prospective authors are invited to email their 8-page papers to cagi07_(on)_cs.okstate.edu by the due date in PDF format. Formatting instructions are given by the conference at http://oregonstate.edu/conferences/icml2007/icml_format_2007.zip. The workshop will not have a blind review process, and therefore author names, affiliations, and contact information should appear in the submission, including postal address, email address, telephone number, and fax number. Electronic versions of the final papers will be available on the workshop home page at www.cs.okstate.edu/cagi07/. Interested participants are also invited to submit 2-page position papers. These will also be peer-reviewed and appear in the workshop proceedings. If the workshop schedule allows, short presentations at the end of the day may be possible as well. Workshop home page: www.cs.okstate.edu/cagi07/ Submit papers to: cagi07_(on)_cs.okstate.edu Important Dates Paper Submission May 7, 2007 Acceptance Notification May 25, 2007 Electronic Proceedings June 15, 2007 Workshop date June 24, 2007 Organizing Committee Istvan Jonyer, Oklahoma State University, USA Pierre Dupont, Université catholique de Louvain, Belgium Tim Oates, University of Maryland Baltimore County, USA Marc Sebban, Université de Saint-Etienne, France Program Committee Pierre Dupont (PC chair), Université catholique de Louvain, Belgium Pieter Adriaans, Universiteit van Amsterdam, The Netherlands Vasant Honavar, Iowa State University, USA Istvan Jonyer, Oklahoma State University, USA Laurent Miclet, Université de Rennes, France Tim Oates, University of Maryland Baltimore County, USA Rajesh Pareck, Iowa State University, USA Yasubumi Sakakibara, Keio University, Japan Marc Sebban, Université de Saint-Etienne, France Menno van Zannen, Macquarie University, Australia Enrique Vidal, Universidad Politécnica de Valencia, Spain ---------------------------- We must attach some meaning - Menno van Zaanen - to the words we use - menno_(on)_ics.mq.edu.au - if we are to speak significantly - www.ics.mq.edu.au/~menno - and not utter mere noise ---------------------------- -Bertrand Russell _______________________________________________ Elsnet-list mailing list Elsnet-list_(on)_elsnet.org http://mailman.elsnet.org/mailman/listinfo/elsnet-list
 

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