Machine Learning List: Vol. 15, No. 4 Saturday, March 1, 2003 Contents Calls for Papers and Other Meeting Announcements HLT/NAACL 2003 CFP: CoNLL-2003 7th Conf on Natural Language Learning HLT/NAACL-2003 Workshop CFP: Building and Using Parallel Texts: Data Call for Tutorial Proposals Call for Special Session Proposals Workshop: Learning from Imbalanced Data Sets DATE CHANGE: Wrkshp on Advances in ML, Montreal, June 9-13, 2003 DMLL: ML journal Special issue on Data Mining Lessons Learned Call for papers - ICMLC-2003 Extended Deadline: IJCAI-03 Workshop on ... Web Personalization EXTENDED DEADLINE: HLT/NAACL-2003: Text Summarization ... (DUC-2003) ICML Workshop on Machine Learning for Space EXTENSION: IJCAI'03 Wrkshp Mixed-Initiative Intelligent Systems The Machine Learning List is moderated. Contributions should be relevant to the scientific study of machine learning. Please send submissions for distribution to: ml@isle.org. For requests to be added, removed, or to change your email address, send email to: ml-request@isle.org. In general, submissions should be no more than a few full-screens of text. For meeting announcements, highlight the conference or workshop web page and give a summary description of the goals of the event. Information such as the list of program committee members, talk schedules, and registration forms are unnecessary and should not be included. Job adds are usually no more than a few full-screens so they should fit naturally. ---------------------------------------------------------------------- From: Priscilla Rasmussen Subject: HLT/NAACL 2003 CFP: CoNLL-2003 7th Conf on Natural Language Learning Date: Mon, 10 Feb 2003 11:44:19 EST CALL FOR PAPERS CoNLL-2003: Seventh Conference on Natural Language Learning Organized at HLT-NAACL-02, Edmonton, Canada May 31 - June 1 2003 http://cnts.uia.ac.be/conll2003/ CoNLL is an international forum for discussion and presentation of research on natural language learning. We invite submission of papers about natural language learning topics, including, but not limited to: - Computational models of human language acquisition - Computational models of the origins and evolution of language - Machine learning methods applied to natural language processing tasks (speech processing, phonology, morphology, syntax, semantics, discourse processing, language engineering applications) - Symbolic learning methods (Rule Induction and Decision Tree Learning, Lazy Learning, Inductive Logic Programming, Analytical Learning, Transformation-based Error-driven Learning) - Biologically-inspired methods (Neural Networks, Evolutionary Computing) - Statistical methods (Bayesian Learning, HMM, maximum entropy, SNoW, Support Vector Machines) - Reinforcement Learning - Active learning, ensemble methods, meta-learning - Computational Learning Theory analysis of language learning - Empirical and theoretical comparisons of language learning methods - Models of induction and analogy in Linguistics See http://www.aclweb.org/signll and http://ilk.uvt.nl/~signll/conll.html for more information about SIGNLL and CoNLL. SPECIAL THEME As in previous years, in addition to submissions on the general topics listed above, we encourage submissions on a special theme. This year's special theme is: Semi-supervised / unsupervised learning and sample selection techniques for language learning (co-training, active learning, EM, etc). Supervised Machine Learning methods suffer from a "data annotation bottleneck" which is especially harmful for language learning tasks where a lot of training data is needed (e.g. parsing). Sample selection techniques, and combination of supervised learning with semi-supervised and unsupervised techniques may provide a solution to this problem. SHARED TASK This year's workshop will also accept submissions for a shared task: machine learning approaches to named entity recognition. Special attention will be given to the use of multiple sources of knowledge, like training data, lists of examples and unannotated data. Interested groups will be supplied with the same training and testing material (in several languages), and will all use the same evaluation criteria, thus allowing comparison between various learning methods. More information on the shared task will be available at: http://cnts.uia.ac.be/conll2003/ner/ IMPORTANT DATES Deadline for Paper Submission: March 16, 2003 Deadline for Shared Task Submission: March 16, 2003 Notification: March 24, 2003 Deadline camera-ready paper: April 10, 2003 Conference: May 31-June 1 2003 ------------------------------ From: Priscilla Rasmussen To: rasmusse@cs.rutgers.edu Subject: HLT/NAACL-2003 Workshop CFP: Data Driven Machine Translation Date: Mon, 10 Feb 2003 11:50:43 EST C A L L F O R P A P E R S Building and Using Parallel Texts: Data Driven Machine Translation and Beyond An HLT-NAACL 2003 Workshop Edmonton, Alberta May 31 or June 1, 2003 http://www.cs.unt.edu/~rada/wpt The goal of this workshop is to provide a forum for researchers working on problems related to the creation and use of parallel text. Recent events have demonstrated once again the importance of inter-language communication, and reinforce the need for advances in machine translation (MT) and multi-lingual processing tools. The workshop will be centered around the problem of building and using parallel corpora, which are vital resources for efficiently deriving multi-lingual text processing tools. In addition to regular papers, the workshop also includes a shared task that will result in a comparative evaluation of word alignment techniques. While we invite submissions addressing any of the above topics, or related issues, we particularly welcome work involving parallel corpora addressing languages with scarce resources. SHARED TASK: All researchers who have a word alignment system available are invited to participate in the shared task, individually or as part of a team. Participants in the shared task will be provided with common sets of training data, consisting of Romanian-English and French-English parallel texts. Participants will be given approximately one month to train their systems with this data, and then previously held out test data will be released. Participants will run their alignment system on this test data and submit their results, which will be evaluated using a common set of metrics. See the workshop website for details regarding the shared task. IMPORTANT DATES: Deadline for regular paper submissions: March 10 Deadline for results submissions: March 25 (shared task) Deadline for short paper submissions: April 1 (shared task) Notification of acceptance for regular papers: April 1 Deadline for camera-ready papers: April 10 ------------------------------ From: Eugene Eberbach Subject: Call for Tutorial Proposals Date: Mon, 10 Feb 2003 17:33:55 -0500 CEC2003 - Congress on Evolutionary Computation Canberra, Australia, December 8-12, 2003 http://www.cs.adfa.edu.au/cec_2003/ The Program Committee of CEC2003 welcomes proposals for tutorials on all aspects of evolutionary computation and its applications, or closely related fields. Tutorials should be a means for senior researchers to present an overview of a field related to evolutionary computation. A tutorial should not be a technical presentation focusing on ones own work only. It should preferably handle a relatively large chunk of knowledge on a specific area, typically at an introductory level. Comprehensive references must also be provided. IMPORTANT DATES April 4, 2003: Deadline for tutorial proposals May 2, 2003: Notification of tutorial acceptance Sept. 15, 2003: Electronic version of tutorial notes due (PostScript, PDF, Word or PowerPoint) Dec. 8-12, 2003: CEC2003 SUBMISSION DETAILS Proposals for tutorials should be one page in length and should contain the following information: 1. Title 2. Name and full contact information of the proposer(s), together with one paragraph explaining why she/he/they is/are the right person for that topic. 3. A brief description (one or two paragraphs) of the intended contents. 4. The preferred length of their tutorial (2h, 3h, or 4h, knowing that not all wishes will come true) 5. Any resource requirements, e.g. computers, equipment setup, 3D projector, etc. 6. An optional label being either "novice" (e.g. Intro to GP) or "advanced" (e.g. Recent advances in parallel GAs). Proposals should be sent in plain ASCII (iso8859-1) TEXT format to both the tutorial chairs mkirley@postoffice.csu.edu.au, Marc.Schoenauer@inria.fr no later than April 4. 2003. ------------------------------ From: Eugene Eberbach Subject: Call for Special Session Proposals Date: Mon, 10 Feb 2003 17:37:12 -0500 CEC2003 - Congress on Evolutionary Computation Canberra, Australia, December 8-12, 2003 http://www.cs.adfa.edu.au/cec_2003/ CEC'03 is now inviting special session proposals. All special sessions are to be organized around a specific topic in order to encourage in-depth discussions. Special sessions will be an integral part of the conference. All accepted papers in the special sessions will be included in the published conference proceedings. All special session papers will be reviewed, and the review process will be coordinated and supervised by the special session organizer(s). Each proposal should contain at least the following information: (1) Title of the session; (2) Name of the organizer(s) and their detailed contact addresses; (3) One or two paragraphs describing the theme and topics covered by the session. The accepted special sessions will be posted and updated regularly on the conference homepage (http://www.cs.adfa.edu.au/cec_2003.html). To propose a special session, email your proposal to Dr KC Tan (eletankc@nus.edu.sg), CEC'03 Special Sessions Co-Chair. ------------------------------ From: Nathalie Japkowicz Subject: Workshop: Learning from Imbalanced Data Sets Date: Tue, 11 Feb 2003 12:30:17 -0500 (EST) CALL FOR PAPERS ICML-KDD'2003 Workshop: Learning from Imbalanced Data Sets II Thursday, August 21, 2003 Washington, DC WORKSHOP PAGE: http://www.site.uottawa.ca/~nat/Workshop2003/workshop2003.html OVERVIEW: Recent years brought increased interest in applying machine learning techniques to difficult "real-world" problems, many of which are characterized by imbalanced learning data, where at least one class is under-represented relative to others. Examples include (but are not limited to): fraud/intrusion detection, risk management, medical diagnosis/monitoring, bioinformatics, text categorization and personalization of information. The problem of imbalanced data is often associated with asymmetric costs of misclassifying elements of different classes. Additionally the distribution of the test data may differ from that of the learning sample and the true misclassification costs may be unknown at learning time. The AAAI-2000 Workshop on "Learning from Imbalanced Data Sets" provided the first venue where this important problem was explicitly addressed and has been received with much interest. The related ICML-2000 Workshop on "Cost-Sensitive Learning" provided another venue for addressing the problem of asymmetric costs of different classes and features. Although much awareness of the issues related to data imbalance has been raised, many of the key problems still remain open and are in fact encountered more often, especially when applied to massive datasets. We believe that it would be of value to the machine learning community to not only examine the progress achieved in this area over the last three years but also discuss the current school of thought on research in learning from imbalanced datasets. Based on our understanding of class imbalance problem, the following topics of discussion are proposed (but not limited to): * sampling (under-, over-, progressive, active) * post-processing of learned models * accounting for class imbalance via inductive bias * one-sided learning * handling uncertainty of target distribution and misclassification costs * handling varying amounts (class dependent) of label noise SUBMISSIONS: Authors are invited to submit papers on the topics outlined above or on other related issues. Submissions should not exceed 8 pages, and should be in line with the ICML style sheet. Electronic submissions, in PDF format, are prefered and should be sent to: Nitesh Chawla at chawla@morden.csee.usf.edu TIMETABLE: Submission deadline: May 1, 2003 Notification date: May 25, 2003 Final date for camera-ready copies to organizers: June 8, 2003 ------------------------------ From: Balazs Kegl Subject: DATE CHANGE: Wrkshp on Advances in ML, Montreal, June 9-13, 2003 Date: Tue, 11 Feb 2003 14:16:56 -0500 Due to a date conflict with a major conference, we have had to reschedule the Workshop on Advances in Machine Learning from June 2-6 to June 9-13. We apologize for the inconvenience it may cause. The paper submission deadline remains March 31. Call for papers Workshop on Advances in Machine Learning Montreal, Canada, June 9-13, 2003 URL: www.iro.umontreal.ca/~lisa/workshop2003.html IMPORTANT DATES: March 31, Paper submission deadline April 15, Notification of paper acceptance/rejection. ------------------------------ From: Hiroshi Motoda Subject: DMLL: ML journal Special issue on Data Mining Lessons Learned Date: Tue, 18 Feb 2003 15:44:22 +0900 Machine Learning Journal: Special Issue on Data Mining Lessons Learned http://www.hpl.hp.com/personal/Tom_Fawcett/DMLL-MLJ-CFP.html Guest editors: Nada Lavrac, Hiroshi Motoda and Tom Fawcett Submission deadline: Monday, 7 April, 2003. CALL FOR PAPERS Data mining is concerned with finding interesting or valuable patterns in data. Many techniques have emerged for analyzing and visualizing large volumes of data, and what we see in the technical literature are mostly success stories of these techniques. We rarely hear of steps leading to success, failed attempts, or critical representation choices made; and rarely do papers include expert evaluations of achieved results. Insightful analyses of successful and unsuccessful applications are crucial for increasing our understanding of machine learning techniques and their limitations. Challenge problems (such as the KDD Cup, COIL and PTE challenges) have become popular in recent years and have attracted numerous participants. These challenge problems usually involve a single difficult problem domain, and participants are evaluated by how well their entries satisfy a domain expert. The results of such challenges can be a useful source of feedback to the research community. At ICML-2002 a workshop on Data Mining Lessons Learned was held and (http://www.hpl.hp.com/personal/Tom_Fawcett/DMLL-workshop.html) and was well attended. This special issue of the Machine Learning journal follows the main goals of that workshop, which are to gather experience from successful and unsuccessful data mining endeavors, and to extract the lessons learned from them. SUBMISSION INSTRUCTIONS Manuscripts for submission should be prepared according to the instructions at http://www.cs.ualberta.ca/~holte/mlj/ In preparing submissions, authors should follow the standard instructions for the Machine Learning journal at http://www.cs.ualberta.ca/~holte/mlj/initialsubmission.pdf Submissions should be sent via email to Hiroshi Motoda (motoda@ar.sanken.osaka-u.ac.jp), as well as to Kluwer Academic Publishers (jml@wkap.com). In the email please state very clearly that the submission is for the special issue on Data Mining Lessons Learned. ------------------------------ From: "Jacobus van Zyl" Subject: Call for papers - ICMLC-2003 Date: Wed, 19 Feb 2003 12:34:37 +0100 Call for Papers International Conference on Machine Learning and Cybernetics 2003 Sponsored by Machine Learning Centre Hebei University, Baoding, Hebei, China and IEEE Systems, Man and Cybernetics Technical Committee on Cybernetics 24-27 August 2003 Xi-an, China The second International Conference on Machine Learning and Cybernetics (ICMLC-2003) sponsored by the Machine Learning Centre of the Hebei University (www.hbu.edu.cn) and the IEEE Systems, Man and Cybernetics Technical Committee on Cybernetics (www.isye.gatech.edu/ieee-smc), will be held in Xi-an, China on 24-27 August 2003. We are living in a world which is rapidly evolving from an information-based to a knowledge-based society. In this new environment, we must be able to effectively turn the data we have into knowledge for our survival and advancement. Machine learning plays an important role in helping us generate new knowledge from data, whereas cybernetics provides a framework for the applications and implementations. This conference will bring together researchers, as well as people and organizations interested in machine learning and cybernetics applications, to exchange ideas and report progress in this important and exciting area of research and development. TOPICS FOR SUBMISSION: We invite original papers in machine learning an cybernetics including, but not limited to the following topics: * Adaptive Systems * Information Retrieval * Artificial Neural Networks * Intelligent Agents * Approximate Reasoning * Intelligent DSS * Case-Based Reasoning * Intelligent Control Systems * Data-Mining * Knowledge Based Systems * Evolutionary Computation * Knowledge Representation * Feature Selection * Pattern Recognition * Fuzzy Control * Speech Recognition * Fuzzy Systems and Theory * Support Vector Machines * Hybrid Systems * Wavelet & Multi-Resolution * Inductive Learning * Web-Mining Machine Learning Applications in: * Bio-Informatics * Construction Project Management * Financial Engineering * Geo-Informatics * Intelligent Transportation Systems * Logistics * Medical Informatics * Natural Language Processing * Network Intrusion Detection * Power Supply IMPORTANT DATES: Submissions due: 15 April 2003 Notification of acceptance: 15 June 2003 Camera-ready copies of accepted papers due: 15 July 2003 Conference: 24-27 August 2003 Conference Website (under construction): http://www.icmlc2003.hbu.edu.cn ------------------------------ From: "Sarabjot Singh Anand" Subject: Extended Deadline: IJCAI-03 Workshop on ... Web Personalization Date: Sun, 23 Feb 2003 22:52:42 -0000 The IJCAI 2003 Workshop on Intelligent Techniques for Web Personalization (ITWP '03) will be held on Monday, August 11, 2003 in Acapulco, Mexico Since the publishing of the first call for papers, we have recieved confirmation from Elsevier of the acceptance of our proposal for a post-workshop book on Intelligent Techniques for Web Personalisation as part of the Lecture Notes in Artificial Intelligence (State-of-the-Art Survey) series. The best papers from the workshop will be invited to submit chapters for publication in the book. In view of this development we have decided to Extend the Deadline for papers. Important Dates and Deadlines Abstract Submission: March 14, 2003 Full Paper Submission: March 21, 2003 Notification of Acceptance: April 20, 2003 Camera Ready Papers Due: May 23, 2003 For additional information on the workshop please visit the workshop web site at: http://maya.cs.depaul.edu/~mobasher/itwp03/ which will provide additional details including the Topics of interest, paper format requirements and the programme committee. Also please feel free to e-mail the workshop co-chairs for any questions that remain unanswered. ------------------------------ From: Priscilla Rasmussen Subject: EXTENDED DEADLINE: HLT/NAACL-2003: Text Summarization ... (DUC-2003) Date: Wed, 26 Feb 2003 17:14:26 EST !!SUBMISSION DEADLINE EXTENDED TO MARCH 7, 2003!! HLT-NAACL Text Summarization Workshop and Document Understanding Conference (DUC 2003) May 31 and June 1, 2003 Edmonton, AB, Canada http://www.umich.edu/cl/hlt-naacl-duc03/ Given that the ACL'03 deadline is tomorrow and that most other HLT-NAACL'03 workshop deadlines are not until early March, the submission deadline for the HLT-NAACL'03 has been extended by a week to March 7. REVISED SCHEDULE - March 7, 2003 - submissions due - March 28, 2003 - authors notified - April 10, 2003 - camera-ready papers due Please visit the workshop site for submissions details and additional information. ------------------------------ From: Kiri Wagstaff Subject: ICML Workshop on Machine Learning for Space Date: Thu, 27 Feb 2003 09:41:48 -0500 (EST) Call for Papers and Participation: ICML-2003 Workshop Machine Learning Technologies for Autonomous Space Applications Thursday, August 21, 2003, Washington, D.C. http://www.lunabots.com/icml2003/ Submission deadline: May 1, 2003 The ICML 2003 workshop on Machine Learning Technologies for Autonomous Space Applications invites contributions from researchers and practitioners in machine learning, space science, and mission planning. This workshop aims to bring together those interested in developing novel machine learning algorithms for autonomous spacecraft with those concerned with misson safety, performance, and engineering constraints to bridge the "applicability divide". Despite progress in developing applicable ML techniques, adoption and integration into fielded remote space missions remains a challenge. The workshop will provide a context for mission engineers and scientists to present their "wish lists" and real-world constraints to machine learning researchers and for ML scientists to present pertinent, cutting-edge technologies. The ultimate goal is to foster research and development leading to the application of machine learning methods on real, flown spacecraft. We convene this workshop as a forum where we can address critical questions such as: * How can we design algorithms that can train for a long time under controlled situations, but must work almost perfectly in a remote, autonomous setting? * How can ML techniques be tested so as to convince someone outside the field that they are reliable, robust, and effective for real space systems? What are the best analogue problems and situations, here on Earth, for the development and study of applicable ML techniques? * Are there specific, possibly novel, metrics and methodologies for evaluation that would be most appropriate for these problems? * What ML algorithms drawn from other domains (e.g., tasks with a high cost of failure) are applicable to the problems faced by fielded space missions? * Can we provide formal performance guarantees for ML algorithms in the constrained and sometimes hostile environments in which remote space systems will exist? * How can we strengthen connections between ML researchers and the people making operational decisions for space missions? For a full description of the workshop focus and goals, visit the website at http://www.lunabots.com/icml2003/ . Important Dates: May 1, 2003: Technical submissions due May 25, 2003: Notification of acceptance June 6, 2003: Camera ready copies due August 1, 2003: Attendance-only submissions due ------------------------------ From: "David W. Aha" Subject: EXTENSION: IJCAI'03 Wrkshp Mixed-Initiative Intelligent Systems Date: Thu, 27 Feb 2003 10:31:58 -0500 This is to announce a revised submission deadline for this workshop IJCAI'03 Workshop on Mixed-Initiative Intelligent Systems Acapulco, Mexico, August 9th, 2003 Submission deadline: March 16th, 2003 http://lalab.gmu.edu/MIIS/default.htm ------------------------------ End of ML-LIST Digest Vol 15, No. 4 ***********************************