Machine Learning List: Vol. 15, No. 5 Monday, Mar 17, 2003 Contents Calls for Papers and Other Meeting Announcements Call for papers - Special session on Learning Soccer Agents (SMC'03) Cognitive Science conference, Sydney July 13-17 DATE CHANGE: Workshop on Advances in Machine Learning, June 8-11, 03 Career Opportunities Machine learning job openings at RIACS/NASA Ames PhD Studenship Offer Misc Other Announcements clustering of all Machine Learning in Medicine articles SIGKDD Explorations Volume 4, Issue 2 available online 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: "Tomoharu Nakashima" Subject: Call for papers - Special session on Learning Soccer Agents (SMC'03) Date: Tue, 4 Mar 2003 05:37:59 +0900 CALL FOR PAPERS Special Session on Learning Soccer Agents IEEE International Conference on Systems, Man, and Cybernetics (SMC'03) https://becat.engr.uconn.edu/IEEE_CSMC_2003/ We are organizing a special session in the IEEE International Conference on Systems, Man, and Cybernetics (SMC'03). The theme of the special session is "Learning Soccer Agents". The scope of this special session is to present papers that apply a learning method to soccer agents (either hardwares or softwares). Examples of the research topics include, but are not limited to: Multi-agent systems, Distributed autonomous systems, Machine learning (Decision trees, rule-based systems, etc.), Neural networks, Evolutionary computation, Fuzzy systems, Reinforcement learning, Statistical learning theory, and Game theory. We would like to invite you (or a member of your group) to contribute a paper for this session. If you are interested, please send the followings to me (nakashi@ie.osakafu-u.ac.jp) as soon as possible: (1) The title, (2) The author(s) and affiliation(s), (3) The corresponding author's contact information (E-mail address, postal address, and phone & FAX numbers), and (4) One-page abstract (pdf format). IMPORTANT DAYS April 5, 2003: One-page abstract submission due May 5, 2003: Acceptance notification June 23, 2003: Camera-ready paper submission due Although five papers are expected to be included in the special session, we can accomodate more papers to form a special 'track' on the theme. ------------------------------ From: Peter Slezak Subject: Cognitive Science conference, Sydney July 13-17 Date: Sat, 8 Mar 2003 12:58:08 +1100 Announcement and Call for Papers COGNITIVE SCIENCE Joint International Conference 4th ICCS International Conference on Cognitive Science 7th ASCS Australasian Society for Cognitive Science Conference 13-17 July, 2003 The University of New South Wales Sydney, Australia http://www.cogsci.unsw.edu.au DEMONSTRATION Sony Legged Robots 'ROBOCUP' 2001, 2002 World Champion UNSW Team SUBMISSIONS We invite submissions from all disciplines within Cognitive Science, including: Computer science & Artificial Intelligence Linguistics Neuroscience Philosophy Psychology Anthropology Submissions for papers and posters will be reviewed on the basis of abstracts accepted via our website: http://www.cogsci.unsw.edu.au IMPORTANT KEY DATES *Please note: In case early notice of acceptance is needed, we will provide rapid response to submissions made at any time earlier than the deadlines below: 1 April 2003 Abstracts and proposals for symposia due 1 May 2003 Notice of acceptance or rejection 1 June 2003 Full papers due 13-17 July, 2003 Conference Proposals are invited for special streams and symposia. Planned symposia include: * Music and Cognition * Mental Representation * Cognitive Science and Education * Cognitive Science of Science * Animal Cognition * Decision Making, Risk & Behavioural Finance * Language and Cognition * Brain imaging * Machine Learning * Evolutionary psychology * Historical Foundations of Cognitive Science * Psychiatry, Neuropsychiatry & Psychoanalysis Submission of proposals for symposia and workshops should be emailed to Peter Slezak: p.slezak@unsw.edu.au ------------------------------ From: Balazs Kegl Subject: DATE CHANGE: Workshop on Advances in Machine Learning, June 8-11, 03 Date: Fri, 14 Mar 2003 12:19:21 -0500 An unfortunate coincidence with the Formula-1 race in Montreal (Grand Prix) forces us to shift the Workshop on Advances in Machine Learning from June 9-13 to June 8-11. If you plan to come and you need accommodation, please mail to our local organizer, Louis Pelletier (pelletl@CRM.UMontreal.CA) the earliest possible (hotels are filling up quickly because of the car race even before the 12th). We apologize for the inconvenience the repeated date change may cause. The paper submission deadline remains March 31. Call for papers Workshop on Advances in Machine Learning Montreal, Canada, June 8-11, 2003 URL: www.iro.umontreal.ca/~lisa/workshop2003.html SCOPE: Probabilities are at the core of recent advances in the theory and practice of machine learning algorithms. The workshop will focus on three broad areas where these advances are crucial: statistical learning theory, learning algorithms, and reinforcement learning. The workshop will therefore bring together experts from each of these three important domains. Among the sub-topics that will be covered, we note: variational methods, graphical models, the curse of dimensionality, empirical methods to take advantage of theories of generalization error, and some of the applications of these new methods. On the theoretical side, in recent years a lot of effort has been devoted to explain the generalization abilities of popular learning algorithms such as voting classifiers and kernel methods. Some of these results have given rise to general principles that can guide practical classifier design. Some (non-exclusive) sub-topics in this aspect of the workshop include Rademacher and Gaussian complexities, algorithmic stability and generalization, localized complexities and results on the generalization ability of voting classifiers and kernel-based methods. On the algorithmic side, one of the emphasis of recent years has been on probabilistic models that attempt to capture the complex structure in the data, often by discovering the main lower-dimensional features that explain the data. This raises interesting and difficult questions on how to train such models, but such algorithms may have wide ranging applications in domains in which the data has interesting structure that may be explained at multiple levels, such as in vision and language. In reinforcement learning (RL), recent research has brought significant advances in some of the traditional problems, such as understanding the interplay between RL algorithms and function approximation, and extending RL beyond MDPs. At the same time, new areas of research, such as computational game theory, have developed at the interface between RL and probabilistic learning methods. In this workshop, we invite presentations on all RL topics, ranging from theoretical development to practical applications. IMPORTANT DATES: March 31, Paper submission deadline April 15, Notification of paper acceptance/rejection. ------------------------------ From: "Serdar Uckun" Subject: Machine learning job openings at RIACS/NASA Ames Date: Tue, 4 Mar 2003 09:05:51 -0800 RIACS and NASA Ames Research Center have four job openings for research scientists in the area of Machine Learning with applications in NASA's strategic enterprises. The Research Institute for Advanced Computer Science (RIACS) performs computer science research in collaboration with NASA and university scientists to solve challenging scientific problems in support of NASA's goals and missions. RIACS is located at NASA Ames Research Center in the heart of Silicon Valley. RIACS is an institute of the Universities Space Research Association (USRA), a non-profit organization. See http://www.riacs.edu for further details. The existing openings are: Senior Scientist - Machine Learning Synopsis: R&D in machine learning and data mining; 10 years experience. Job ID: 03-04 Posted: February 12, 2003 Location: Moffett Field, CA Senior Scientist - Machine Learning and Space Sciences Synopsis: R&D in machine learning and data mining; space science background; 5 years experience. Job ID: 03-05 Posted: February 18, 2003 Location: Moffett Field, CA Senior Scientist - Bioinformatics Synopsis: R&D in bioinformatics; strong computer science background; 5 years experience. Job ID: 03-06 Posted: February 18, 2003 Location: Moffett Field, CA Scientist - Bioinformatics and Machine Learning Synopsis: R&D in bioinformatics; strong computer science and machine learning background; 2 years experience. Job ID: 03-09 Posted: February 18, 2003 Location: Moffett Field, CA See http://www.riacs.edu/employment for further details on these positions and instructions on how to apply. ------------------------------ From: Armando Vieira Subject: PhD Studenship Offer Date: Mon, 10 Mar 2003 23:55:45 +0000 A PhD Studentship position for a period of three years is open in Polymer Department at University of Minho, Guimar=E3es, to work on Multiobjective optimisation with evolutionary algorithms using Neural Networks. The objective of the work is to study and develop new methods to increase the performance of Genetic Algorithms in multi-optimization problems through the use of Artificial Neural Networks to speed the search of useful solutions. The work will be applied to the important problem of polymer extrusion. This work uses new and fascinating topics linking concepts from biology, physics and machine learning. The work developed will therefore have a great potential to open new frontiers with a high impact on the scientific community. The candidate will integrate a young and dynamic team with several years of expertise with an active publication record in international referee journals. The Polymer Department has a well established and active research team with several PhD and first quality facilities. The work will take place in the modern Azurem campus at Guimar=E3es, with excellent working conditions including computer facilities and access to bibliography. Guimar=E3es is a beautiful historic city at the heart of the exuberant Minho province, north of Portugal, classified by UNESCO as World Patrimony. Although a small and relaxing city, Guimar=E3es has an important student community that brings its streets full of live. Profile required: Bachelor or Master in Physics, Material Science or Computer Science with knowledge programming on C language and good analitic skills. Project supervisors: Prof. Ant=F3nio Gaspar-Cunha and Armando Vieira. Submissions Deadline: 15 April For more information contact A. Gaspar: Phone: +351 253 510328 gaspar@dep.uminho.pt http://www.dep.uminho.pt=20 ------------------------------ From: Raul Valdes-Perez Subject: clustering of all Machine Learning in Medicine articles Date: Sun, 2 Mar 2003 08:13:05 -0500 Hi, this URL may be of interest to ML list subscribers: http://vivisimo.com/search?v:file=ML_in_Medicine It's an automatic hierarchical clustering of all PubMed articles that mention Machine Learning. Cordially, Raul Valdes-Perez ------------------------------ From: Sunita Sarawagi Subject: SIGKDD Explorations Volume 4, Issue 2 available online Date: Wed, 12 Mar 2003 23:17:09 +0530 We are please to announce that the SIGKDD Explorations Volume 4, Issue 2 is available online at: http://www.acm.org/sigkdd/explorations/ Johannes Gherke served as Guest Editor for this issue and coordinated a set of high-quality articles on the topic of Privacy and Security issues in data mining. This issue also includes writeups from the winning entries of last year's KDD Cup competition and reports of other events from KDD 2002. Table of Contents: Contributed Articles on Privacy and Security Data Mining, National Security, Privacy and Civil Liberties B. Thuraisingham The Inference Problem: A Survey C. Farkas and S. Jajodia Cryptographic Techniques for Privacy-Preserving Data Mining B. Pinkas Database Privacy M. Olivier Tools for Privacy Preserving Data Mining C. Clifton, M. Kantarcioglu, J. Vaidya, X. Lin and M.Y. Zhu Applying Data Mining to Intrusion Detection: The Quest for Automation, Efficiency, and Credibility W. Lee Randomization in Privacy-Preserving Data Mining A. Evfimievski Contributed Articles A Survey on Wavelet Applications in Data Mining T. Li, Q. Li, S. Zhu, and M. Ogihara A Perspective on Inductive Databases L. De Raedt The True Lift Model - A Novel Data Mining Approach to Response Modeling in Database Marketing V. S. Y. Lo Reports from KDD-2002 Background and Overview for KDD Cup 2002 Task 1: Information Extraction from Biomedical Articles A. Yeh, L. Hirschman, A. Morgan Rule-based Extraction of Experimental Evidence in the Biomedical Domain - the KDD Cup (Task 1) Y. Regev, M. Finkelstein-Landau, and R. Feldman A Machine Learning Approach for the Curation of Biomedical Literature - KDD Cup 2002 (Task 1) S.S. Keerthi, C.J. Ong, K.B. Siah, D.B.L. Lim, W. Chu, M. Shi, D. S. Edwin, R. Menon, L. Shen, J.Y.K. Lim, and H.T. Loh Automatic Scientific Text Classification Using Local Patterns: KDD CUP 2002 (Task 1) M. M. Ghanem, Y. Guo, H. Lodhi, and Y. Zhang The Genomics of a Signaling Pathway: A KDD Cup Challenge Task M. Craven One Class SVM for Yeast Regulation Prediction A. Kowalczyk and B. Raskutti Predicting the Effects of Gene Deletion D. S. Vogel and R. C. Axelrod Combining Data and Text Mining Techniques for Yeast Gene Regulation Prediction: A Case Study M.-A. Krogel, M. Denecke, M. Landwehr, and T. Scheffer Feature Engineering for a Gene Regulation Prediction Task G. Forman P-tree Classification of Yeast Gene Deletion Data A. Perera, A. Denton, P. Kotala, W. Jockheck, W. V. Granda, and W. Perrizo Report on the SIGKDD-2002 Panel The Perfect Data Mining Tool: Interactive or Automated M. Ankerst BIOKDD 2002: Recent Advances in Data Mining for Bioinformatics M. J. Zaki, J. T. L. Wang, H. T. T. Toivonen KDD-2002 Workshop Report Fractals and Self-similarity in Data Mining: Issues and Approaches J. Adibi and C. Faloutsos MDM/KDD2002: Multimedia Data Mining between Promises and Problems S. J. Simoff and C. Djeraba Multi-Relational Data Mining: a Workshop Report S. Dzeroski and L. De Raedt WEBKDD 2002 - Web Mining for Usage Patterns & Profiles B. M. Masand, M. Spiliopoulou, J. Srivastava, and O. R. Zaiane ------------------------------ End of ML-LIST Digest Vol 15, No. 5 ***********************************