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诸葛曹操金虫 (著名写手)
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[交流]
CFP Bayesian Methods for Natural Language Processing at NIPS2005
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CALL FOR PAPERS Bayesian Methods for Natural Language Processing Workshop at the Neural Information Processing Systems Conference (NIPS 2005) http://www.isi.edu/~hdaume/BayesNLP/ ** Submission Deadline: 21 October 2005 ** ************************************************************************ [ Apologies for multiple postings ] OVERVIEW -------- Models of natural language processing problems are often incredibly complex, and there is never enough data to properly estimate all the required parameters. This has lead to a strong need for learning techniques with built-in capacity control; most classical solutions to this problem involve largely ad-hoc smoothing techniques. The application of Bayesian learning methods to these problems could potentially result in more effective models, for which extensive cross-validation is no longer required for hyperparameter tuning or model selection. The goals of this workshop are to bring together researchers from both the Bayesian machine learning community and the natural language processing community to enable cross-fertilization of techniques, models and applications. We wish to focus on the following issues: * Statistical Models: Current Bayesian models for text have largely focused on "bag of words" style approaches, where conditional independence is assumed between words. This leads to a convenient interpretation of a document as a sequence of draws from multinomial distributions, but does not account for any of the internal structure that exists in documents and which NLP researchers are interested in. How can we build models that move beyond the bag of words assumption? What structures are useful for modeling? How can we model these structures efficiently? Can we learn these models automatically? * Applications-oriented Models: Many statistical models for text have aimed at automatically inferring implicit relationship between varied elements of documents in a corpus. How can we use such models to aid in applications? Can we develop similar models that are aimed at solving a real-world NLP task? For what NLP applications are Bayesian techniques appropriate and how can we develop models specific to these problems? CALL FOR PARTICIPATION ---------------------- We invite submission of workshop papers that discuss ongoing or completed work dealing with Bayesian techniques applied to natural language processing problems (see below for an incomplete list of possible topics). A workshop paper should be no more than six pages in the standard NIPS format. Authorship should not be blind. Please submit a paper by emailing it in Postscript or PDF format to hdaume@isi.edu with the subject line "BNLP Submission". We anticipate accepting four to six such papers for 15 minute presentation slots (exact details will be worked out shortly). Please only submit an article if at least one of the authors will be able to attend the workshop and present the work. We are especially interested in submissions from authors in the NLP community who have not previously attended a NIPS conference. If you fall into this category, please note this in your email when you submit your paper. Relevant Topics: * Models that move beyond the bag-of-words assumption * Techniques that apply to problems other than language modeling * Structure-learning techniques for language * Bayesian extensions to well-known NLP models * Application of Bayesian techniques to NLP problems * Both supervised and unsupervised techniques are welcome We also welcome position papers of at most two pages in length that discuss, with appropriate argumentation, whether or not Bayesian techniques are applicable to NLP problems and, if so, which ones. These should be submitted in the same way as standard workshop papers. These will be used to help guide discussion during panel sessions. IMPORTANT DATES --------------- 18 Aug 05 -- Call for participation 21 Oct 05 -- Paper submission deadline 4 Nov 05 -- Notification of paper acceptance 25 Nov 05 -- Survey and position paper deadlines 9/10 Dec 05 -- Workshop in Whistler RESEARCHER SURVEY ----------------- Regardless of whether you submit a paper or not, if you are a researcher in either the Bayesian learning community or the NLP community, please complete our survey (available on the web page), which will serve to guide the panel discussions at the workshop. ORGANIZATION ------------ Hal Daume III Information Sciences Institute hdaume@isi.edu http://www.isi.edu/~hdaume/ Yee Whye Teh National University of Singapore tehyw@comp.nus.edu.sg http://www.cs.berkeley.edu/~ywteh/ [ Last edited by 幻影无痕 on 2006-11-21 at 07:42 ] |
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