linguistlist.org>
Editor for this issue: Anita Huang <anitalinguistlist.org>
justresearch.com>Dear Colleague, This message contains a substantial deadline extension which should give many more of you an opportunity to participate. Please read on. You are invited to participate in the Center for Automated Learning and Discovery workshop on Mixed Media databases. This workshop will be held in conjunction with the Conference on Automated Learning and Discovery, being held at Carnegie Mellon University in Pittsburgh from June the 11th to the 13th 1998. This workshop is intended for researchers with an interest in learning from multiple media. The workshop will emphasize both algorithms and applications of learning with mixed media databases. Papers that describe algorithms should cover either novel approaches designed to benefit from mixed-media data, or modifications of standard algorithms that utilize multiple media data sources. Application papers should clearly demonstrate the benefits of learning from two or more types of media. Different media areas to be addressed include: Vision: Image, Video, and VRML Speech and Audio Text, including OCR, Closed-Captioning, handwriting, and web-documents Olfactory perception Haptic and Touch sensing If you would like to present at this workshop, please submit a paper describing original research work and results. Four copies of the paper should be submitted in hardcopy by April the 5th, 1998. Because of the deadline extension, submissions should be sent, in quadruplicate, to: CALD Workshop on Mixed Media Databases Attn: Michael Witbrock Justresearch 4616 Henry St, Pittsburgh PA 15213 The ideal paper should cover two or more topics listed above and apply some aspect of learning to the multiple media data. The learning may involve, but is not limited to neural networks, as well as statistical and probabilistic models. All statistical, probabilistic, and learning approaches are welcome. Papers submitted to this workshop may also be submitted to other conferences or to journals. If you plan to submit a paper or attend, please contact the organizers (listed below). Detailed submission instructions can be found at the following URL, but you should remember the altered deadline and submission address given above: http://www.cs.cmu.edu/~conald/call.shtml Selected papers from the workshop will be considered for publication in an upcoming special issue of IEEE Expert journal. Organizers: Shumeet Baluja (balujaMail to author|Respond to list|Read more issues|LINGUIST home page|Top of issue
cl.cam.ac.uk>EVOLUTIONARY COMPUTATIONAL LINGUISTICS COLING-ACL '98 WORKSHOP 16th August 1998 University of Montreal Montreal Quebec Canada CALL FOR PAPERS There has been a recent resurgence of interest in the application of evolutionary theory to the understanding of language development, typology, acquisition and change, and to the development of NLP systems. Two significant developments potentially distinguish this new work from that undertaken 100 years or so ago (and ultimately banned by the French Philological Society). Firstly, a rich body of mathematical work in population genetics, (non-linear) dynamic systems, game-theoretic models of evolution, and so forth has since been developed by theoretical biologists, complexity theorists and others. Secondly, the study of evolutionary processes has been further enhanced by the use of computational modelling techniques (in the simulation of adaptive behaviour, artificial life, etc.) which have enabled researchers to gain insight into processes too complex for full mathematical analysis. Evolutionary computation (in the form of genetic algorithms, genetic programming, hybrids of GAs and neural networks, etc.) has also been studied and deployed for practical engineering purposes, including tasks such as grammar induction, disambiguation, and so forth. The evolutionary approach is of direct relevance to NLP, and computational linguists are in a strong position to make a significant contribution to the development of this research. Synchronic generative linguistics models a language as a static well-formed (grammatical) set of strings (sentences) focussing on the (ideal) individual speaker and her idiolect at a single moment in time. Much of current NLP technology is based on implementation of generative models of idiolects and is consequently brittle when it comes into contact with the reality of language variation and language change across idiolects and across time. The crucial shift in perspective provided by the evolutionary approach is to study *changing populations* of (ideal, generative) speakers. Once this step has been taken, language is naturally modelled as a dynamic system emergent from individual idiolects: variation between idiolects interacts with the process of language learning, leading to `imperfect' or selective transmission (inheritance) between generations of speakers. This changes the distribution and composition of idiolects in the population and thus causes some forms of language change. Once it is recognised that `bias' in language learning, production and interpretation creates selection pressure for more learnable, producible and interpretable variants, then it becomes natural to treat language as a (complex) adaptive system responding dynamically to such (often conflicting) pressures. We are soliciting papers on any aspect of evolutionary computation and language for this one-day workshop. We hope that the workshop will stimulate further interest amongst computational linguists and will provide a forum for cross-fertilisation of ideas between those applying evolutionary computation to practical NLP tasks and those using similar techniques to address issues in language acquisition, change and variation. PROGRAM CO-CHAIRS AND ORGANIZING COMMITTEE Bob Berwick (MIT, USA) berwickMail to author|Respond to list|Read more issues|LINGUIST home page|Top of issue