Machine Learning List: Vol. 13, No. 3 Sunday, June 24, 2001 Contents Calls for Papers and Other Meeting Announcements European Workshop on Reinforcement Learning CFPs: NF 2002 (Cuba) and ICAIS 2002 (Australia) Special Issue on Learning Automata IEEE Data Mining 2001: Call for Tutorials Special Issue of JASS journal STACS 2002 Call for papers Call for Papers ICA2001 CFP (Special Issue on Internet Intelligent Systems) NIPS*2001 Call For Workshop Proposals Extended Deadline for MLJ Special Issue, Fusion of Knowledge with Data [CEC2002] First Call for Papers Workshop on Artificial Intelligence for Financial Time Series Analysis Jobs Research Position at Xerox PARC Research Fellow in Computational Data Analysis and Modelling (2 positions) Research Positions available Postdoc opportunity Re: Job Opening Call for Applications: PostDoctoral Research Scientists JOB in Evolutionary Collective Robotics Biostatistician Job Opening in San Francisco, California IDSIA: Two Post DOC Positions in Robotics, Swarm Intelligence and Machine learning Other NEW BOOK! by Lorenzo Magnani Fraud detection bibliography available Special issue on connectionist models for learning in structured JAIR ML-related articles special issue on multi-agent learning WinMine Toolkit version 1.0 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. ---------------------------------------------------------------------- Calls for Papers and Other Meeting Announcements ------------------------------ From: Marco Wiering Subject: European Workshop on Reinforcement Learning Date: Wed, 21 Mar 2001 16:20:01 +0100 (MET) First Call for Participation The Fifth European Workshop on Reinforcement Learning (EWRL5'2001) 5 and 6 October 2001 Utrecht, the Netherlands The biennal European Workshop on Reinforcement Learning (EWRL) will take place in Utrecht, the Netherlands this year. The goal is to gather researchers interested in Reinforcement Learning and its applications. The invited talk will be presented by Prof. Leslie Kaelbling. We encourage the submission of a 2-page abstract, on any aspect of Reinforcement Learning including (but not restricted to): Theoretical aspects of reinforcement learning Function approximation in reinforcement learning Exploration in reinforcement learning Direct vs. Indirect reinforcement learning Multi-agent reinforcement learning Robotic reinforcement learning Novel algorithms for reinforcement learning Reinforcement learning for complex problem solving Reinforcement learning for dynamic replanning Reinforcement learning and game theory Important dates: Submission deadline : 1 August 2001 Acceptance/rejection notification : 3 September 2001 Presentations at EWRL : 5/6 October 2001 For further information, we refer to the website: http://www.cs.uu.nl/~marco/EWRL5.html We look forward to seeing you at EWRL'2001 this year. Marco Wiering (marco@cs.uu.nl) Marco Dorigo (mdorigo@ulb.ac.be) ------------------------------ From: Nadine Subject: CFPs: NF 2002 (Cuba) and ICAIS 2002 (Australia) Date: Tue, 17 Apr 2001 15:28:18 -0700 CALL FOR PAPERS NF 2002 Cuba First International ICSC-NAISO Congress on Neuro Fuzzy Technologies NF 2002 to be held at the Capitolio di Havana, Havana from January 16 - 19, 2002 submission deadline: May 31, 2001 email secretariat: nf2002@itstransnational.com http://www.icsc-naiso.org/conferences/nf2002/index.html and ICAIS 2002 Australia First International ICSC-NAISO Congress on Autonomous Intelligent Systems ICAIS 2002 to be held at Deakin University, Geelong, Australia February 12 - 15, 2002 submission deadline: June 30, 2001 mail secretariat: icais02@itstransnational.com http://www.icsc-naiso.org/conferences/icais2002/index.html ------------------------------ From: Georgios Papadimitriou Subject: Special Issue on Learning Automata Date: Fri, 20 Apr 2001 22:59:17 +0300 Special Issue on Learning Automata: Theory, Paradigms, and Applications To appear in the IEEE Transactions on Systems, Man and Cybernetics, Part B Learning automata have attracted a considerable interest in the last decade. They are adaptive decision-making devices that operate in unknown stochastic environments and progressively improve their performance via a learning process. They have been initially used by psychologists and biologists to describe the human behavior from both psychological and biological viewpoints. Learning automata have made a significant impact in all areas of engineering, and decision science problems. They can be applied to a broad range of modeling and control problems that are nonlinear and with a high degree of uncertainty. Learning automata have some key features, which make them applicable to a broad range of applications: they combine rapid and accurate convergence with a low computational complexity. The applications of learning automata include: process control, pattern recognition, control of service activity, task scheduling, optimization and classification problems, image processing, diagnosis, computer vision, concept learning, and routing and bandwidth allocation in computer communications networks. The special issue intends to attract papers that report advances in: Learning Automata Theory Applications of Learning Automata Performance Issues of Learning Automata P-, Q- and S-model Learning Automata. Ergodic and Absorbing Learning Automata Discretized Learning Automata Estimator Learning Automata Multilevel Systems of Automata Interconnected Automata Games of Automata Convergence of Learning Algorithms Implementation Issues of Learning Automata PROCEDURE Prospective authors are invited to submit their original and previously unpublished papers to any one of the guest editors by November 1, 2001. The authors are encouraged to submit by e-mail an electronic copy of the paper in word for windows, pdf, or postscript formats. If electronic submission is not possible, six hard copies of the manuscript should be submitted. Contributed papers may not exceed 25 double-spaced single-column pages using font 12 including all figures and illustrations. Submitted papers will undergo the standard review procedures of the IEEE Transactions on Systems, Man and Cybernetics-Part B. SCHEDULE Submission Deadline: November 1, 2001 Author Notification: March 1, 2002 Final Manuscript Due: May 1, 2002 Tentative Publication Date: Late 2002 ------------------------------ From: Ning Zhong Subject: IEEE Data Mining 2001: Call for Tutorials Date: Wed, 25 Apr 2001 21:11:12 +0900 (JST) ---------------------------------------------------------------------- ICDM '01: The 2001 IEEE International Conference on Data Mining Sponsored by the IEEE Computer Society ---------------------------------------------------------------------- San Jose, California, USA November 29 - December 2, 2001 Home Page: http://kais.mines.edu/~xwu/icdm/icdm-01.html IEEE ICDM 2001: Call for Tutorials ********************************** The 2001 IEEE International Conference on Data Mining (ICDM '01) will include tutorials providing in-depth background on specific subjects in data mining. The recency of the data mining field, and the variety of disciplines that are represented, lead to many possibilities for good tutorials: * Short courses on areas of machine learning, databases, or statistics that may be "old hat" to specialists in that discipline, but are new to a majority of the conference attendees. (e.g., An Introduction to Hidden Markov Models). * Surveys of new and developing research areas in data mining. (e.g., Text Mining). * End-to-end descriptions of the practical application of data mining technology (i.e., applications that may be "typical" for a paper, but provide an example of issues faced in a data mining project that would generalize to problems faced by the conference attendees). * An in-depth coverage of a past research breakthrough that is now becoming a mature technology. The topics of interest fall within those described in the conference Call for Papers (http://kais.mines.edu/~xwu/icdm/icdm-01.html). Submission Details ================== The tutorial proposal should include the following: 1. Title and abstract of the tutorial; 2. Intended audience. Include prerequisite knowledge required of the attendees, and the expected areas of interest. (For example, a tutorial on statistics for people applying data mining tools vs. a tutorial on statistics for people building data mining tools); 3. Length of time needed (e.g., half day or full day); and 4. Short biographies of the presenters. Tutorial materials such as handouts and slides should be included if available, but are not required for submission. However, providing such materials will show depth and maturity of the tutorial, and will be a strong factor in the selection process. Please send a soft copy (preferred) of your proposal to clifton@computer.org, or a hard copy to: Dr. Chris Clifton The MITRE Corporation M/S K308, 202 Burlington Rd, Bedford, MA 01730-1420, USA Important Dates =============== June 30, 2001: Tutorial submissions. July 31, 2001: Acceptance notices. August 31, 2001: Camera-ready copy of tutorial handouts. November 29, 2001: ICDM '01 tutorials. ------------------------------ From: Nikitas Assimakopoulos Subject: Special Issue of JASS journal Date: Mon, 07 May 2001 12:19:10 +0300 Journal of Applied Systems Studies Methodologies and Applications for Systems Approaches [ JASS ] http://www.unipi.gr/jass/ JASS announces the Special Issue on : "Living, Evolutionary and Tailorable Information Systems: Development Issues and Advanced Applications" "Living systems" is a core research area in the Systems Sciences and has been applied in disciplines ranging from biology to manufacturing and economics. It is only recently, however, that the 'living' aspect has been applied to Information Systems (IS) and that dynamic concepts such as evolution and tailorability have been researched. In timely fashion, this special issue explores approaches to information systems development that promote the ongoing design of systems and/or defer the design process. It is increasingly recognised that business organisations are 'emergent' in the face of change driven by technology, globalisation, deregulation, acquisition and merger, customer relationship management and the like. If you are interested in the above special issue title AND for the current issues, please visit JASS web site. For submission of papers consult the "Aims & Scope" of JASS. ------------------------------ From: Jerome Durand-Lose Subject: STACS 2002 Call for papers Date: Thu, 10 May 2001 20:52:01 +0200 +--------------------+ | STACS 2002 | +--------------------+ 19th International Symposium on Theoretical Aspects of Computer Science Antibes Juan-les-Pins, France March 14--16 2002 http://www.inria.fr/stacs2002 SCOPE: Authors are invited to submit papers presenting original and unpublished research on theoretical aspects of computer science. Typical areas include (but are not limited to): * Algorithms and data structures, including: parallel and distributed algorithms, computational geometry, cryptography, algorithmic learning theory; * Automata and formal languages; * Computational and structural complexity; * Logic in computer science, including: semantics, specification, and verification of programs, rewriting and deduction; * Current challenges, for example: theory, models, and algorithms for biological computing, quantum computing, mobile and net computing. SUBMISSIONS: Authors are invited to submit a draft of a full paper (5-12 pages, the title page must contain a classification of the topic covered, preferably using the list of topics above). The paper should contain a succinct statement of the issues and of their motivation, a summary of the main results, and a brief explanation of their significance, accessible to non-specialist readers. Proofs omitted due to space constraints must be put into an appendix to be read by the program committee members at their discretion. Electronic submission is highly recommended. In case of problems with access to internet, it is possible to submit 6 copies of the draft (plus 1 copy of the appendix) and 15 copies of a one page abstract to the chairperson of the program committee. Detailed information is available on the web site. IMPORTANT DATES: Deadline for submission: September 14, 2001 Notification to authors: November 21, 2001 Final version: December 14, 2001 Symposium: March 14--16, 2002 PROCEEDINGS: Accepted papers will be published in the proceedings of the Symposium (Lecture Notes in Computer Science, Springer-Verlag). Simultaneous submission to other conferences with published proceedings is not allowed. WEB SITE: http://www.inria.fr/stacs2002 ------------------------------ From: Scott Makeig Subject: Call for Papers ICA2001 Date: Wed, 16 May 2001 08:17:25 -0700 (PDT) CALL FOR PAPERS CALL FOR PAPERS ICA2001 http://ica2001.org Third International Conference on Independent Component Analysis and Signal Separation San Diego, California December 9-13, 2001 Independent Component Analysis (ICA) is emerging as a new standard area of signal processing and data analysis. ICA attempts to solve the blind source separation problem in which sensor signals are unknown mixtures of unknown source signals. While there are no general analytical solutions, in the last decade researchers have proposed good approximate methods based on simple assumptions about the source statistics and using maximum likelihood, information maximization and minimization of higher-order moments. ICA theory has received attention from several research communities including machine learning, neural networks, statistical signal processing and Bayesian modeling. More recently numerous applications of ICA have appeared including applications to adaptive speech filtering, speech signal coding, biomedical signal processing, image compression, text modeling and financial data analysis. ICA2001 will feature the latest developments in the new field of blind source separation. The Workshop will feature internationally respected keynote speakers, poster sessions, and symposia on theory, on algorithms and on applications to a wide range of fields and data types. The Conference recreational program includes an informal banquet and a unique opening cocktail party / unmixer. This, the third international meeting in this series, is being hosted by the Institute for Neural Computation, UCSD. The previous two meetings were held in Aussois, France (December, 1999) and Helsinki, Finland (June, 2000). This year's event will be held December 9-13, 2001 immediately following the Neural Information Processing Systems (NIPS) conference in Vancouver, Canada and its post-conference workshops. PAPERS WILL BE ACCEPTED THROUGH THE WORKSHOP WEBSITE http://ica2001.org BETWEEN JUNE 1 AND JUNE 29, 2001 ------------------------------ From: Antonio de Padua Braga Subject: CFP (Special Issue on Internet Intelligent Systems) Date: Thu, 31 May 2001 16:13:51 -0300 ==================================================================== INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE AND APPLICATIONS (IJCIA) http://ejournals.wspc.com.sg/ijcia/ijcia.html SPECIAL ISSUE ON "INTERNET INTELLIGENT SYSTEMS" http://www.cpdee.ufmg.br/~apbraga/se_web.html ==================================================================== IMPORTANT DATES: --------------- - Submission deadline: October 31, 2001 - Notification of acceptance: January 2002 - Publication: June 2002 MAIN TOPICS OF INTEREST: ----------------------- - DATA MINING APPLICATIONS (Electronic commerce, business intelligence, web-based decision support systems, web mining and intelligent, learning database systems, etc). - WEB MINING (Data Mining and Knowledge Discovery, Multimedia Data Mining, Text Mining, Web-Based Ontology Engineering) - WEB INFORMATION RETRIEVAL (Approximate Retrieval, Conceptual Information Extraction, Image Retrieval, Ontology-Based Information Retrieval, Semantic Web, Wrappers, XML) - WEB AGENTS (Information Filtering, Recommender Systems, Remembrance Agents, Web Crawling Agents) CO-EDITORS FOR THE SPECIAL ISSUE: -------------------------------- Prof. Antnio de Pdua Braga Departamento de Engenharia Eletrnica Campus da UFMG (Pampulha) Caixa Postal 209, 30.161-970 Belo Horizonte, MG, Brazil Email: apbraga@cpdee.ufmg.br www.cpdee.ufmg.br/~apbraga Prof. Jason T. L. Wang Data and Knowledge Engineering Laboratory Department of Computer and Information Science New Jersey Institute of Technology University Heights, Newark, New Jersey 07102, USA Email: jason@cis.njit.edu http://www.cis.njit.edu/~jason SUBMISSION GUIDELINES: --------------------- High quality papers on Internet Intelligent Systems, covering applications of Symbolic AI, Neural Networks, Fuzzy, Evolutionary Computation, Hybrid Systems, etc, not restricted to the topics listed above, will be considered for submission. Papers exploring new directions are most welcome. All submitted papers will be reviewed on the basis of technical quality, relevance, significance, and clarity. Electronic submission is encouraged and preferred. Authors are strongly recommended to use Latex to speed-up production of accepted papers, although MS-Word files will also be considered. Papers should not exceed 10 pages in Latex single colunm article style. Please, send PDF or PostScript versions of your paper, and an ASCII version of the cover page (in separate email) to "ijcia@cpdee.ufmg.br". ------------------------------ From: Richard Zemel Subject: NIPS*2001 Call For Workshop Proposals Date: Fri, 1 Jun 2001 14:22:45 -0400 *@* NEW LOCATION: WHISTLER, BC, CANADA *@* Call for Workshop Proposals Neural Information Processing Systems -- Natural and Synthetic NIPS*2001 Post-Conference Workshops -- December 7 and 8, 2001 Whistler/Blackcomb Resort, BC, CANADA http://www.cs.cmu.edu/Web/Groups/NIPS. Following the regular program of the Neural Information Processing Systems 2001 conference in Vancouver, BC, Canada, workshops on various current topics in neural information processing will be held on December 7 and 8, 2001, in Whistler, BC, Canada. We invite researchers interested in chairing one of these workshops to submit workshop proposals. The goal of the workshops is to provide an informal forum for researchers to discuss important research questions and challenges. Controversial issues, open problems, and comparisons of competing approaches are encouraged and preferred as workshop topics. Representation of alternative viewpoints and panel-style discussions are particularly encouraged. Workshop topics include, but are not limited to, the following: Active Learning, Architectural Issues, Attention, Audition, Bayesian Analysis, Bayesian Networks, Benchmarking, Brain Imaging, Computational Complexity, Computational Molecular Biology, Control, Genetic Algorithms, Graphical Models, Hippocampus and Memory, Hybrid Supervised/Unsupervised Learning Methods, Hybrid HMM/ANN Systems, Implementations, Independent Component Analysis, Mean-Field Methods, Markov Chain Monte-Carlo Methods, Music, Network Dynamics, Neural Coding, Neural Plasticity, On-Line Learning, Optimization, Recurrent Nets, Robot Learning, Rule Extraction, Self-Organization, Sensory Biophysics, Signal Processing, Spike Timing, Support Vectors, Speech, Time Series, Topological Maps, and Vision. SUBMISSION INSTRUCTIONS Interested parties should submit a short proposal for a workshop of interest via email by July 8, 2001. Proposals should include title, description of what the workshop is to address and accomplish, proposed workshop length (1 or 2 days), planned format (e.g., lectures, group discussions, panel discussion, combinations of the above, etc.), and proposed speakers. Names of potential invitees should be given where possible. Preference will be given to workshops that reserve a significant portion of time for open discussion or panel discussion, as opposed to pure ``mini-conference'' format. The proposal should motivate why the topic is of interest or controversial, why it should be discussed, and who the targeted group of participants is. It also should include a brief resume of the prospective workshop chair with a list of publications to establish scholarship in the field. We encourage workshops that build, continue, or arise from one or more workshops from previous years. Please mention any such connections. Submissions should include contact name (if there is more than one organizer, please designate one organizer as the ``contact person'') as well as addresses, email addresses, phone and fax numbers for all organizers. Proposals should be emailed as plain text to: nips-workshop-proposal@cs.unm.edu. Please do not use attachments, Microsoft Word, postscript, html, or pdf files. Questions may be addressed to nips-workshop-admin@cs.unm.edu. PROPOSALS MUST BE RECEIVED BY JULY 8, 2001 ------------------------------ From: Richard Dybowski Subject: Extended Deadline for MLJ Special Issue, Fusion of Knowledge with Data Date: Mon, 04 Jun 2001 19:38:41 +0100 ------------------------------------------------------------------------ Machine Learning Journal Special Issue on Fusion of Domain Knowledge with Data for Decision Support ------------------------------------------------------------------------ >>> Extended Deadline <<< Statistics and machine learning are data-oriented tasks in which domain models are induced from data. The bulk of research in these fields concentrates on inducing models from data archived in computer databases. However, for many problem domains, human expertise forms an essential part of the corpus of knowledge needed to construct models of the domain. The discipline of knowledge engineering has focused on encoding the knowledge of experts in a form that can be encoded into computational models of a domain. At present, knowledge engineering and machine learning remain largely separate disciplines. Yet in many fields of endeavor, substantial human expertise exists alongside data archives. When both data and domain knowledge are available, how can these two resources effectively be combined to construct decision support systems? The aim of this special issue of the Machine Learning journal is to allow researchers to communicate their work on integrating domain knowledge with data (knowledge-data fusion; theory revision; theory refinement) to a general machine learning audience. Emphasis is on sound theoretical frameworks rather than ad hoc approaches. Of particular interest are papers that combine clear theoretical discussion with practical examples, and papers that compare different approaches. Possible frameworks for knowledge-data fusion include probabilistic (Bayesian/belief) networks, possibilistic logics and networks, hybrid neuro-fuzzy networks, and inductive logic programming. Topics of interest include (but are not limited to): * Practical applications of knowledge-data fusion. What lessons have been learnt from attempts to apply knowledge-data fusion to real-world decision problems? * How are the various knowledge representation and inference frameworks that permit induction theoretically related to each other? * What frameworks enable an existing induced model, such as a neural network, to be incorporated into a proposed knowledge-based system? * How can knowledge-data fusion be applied to temporal data? Submitted papers must not exceed 30 pages and must conform to the Machine Learning journal style. Please see the associated Web site for further submission details: http://www.dybowski.com/kdfml/ This Call for Papers is *not* restricted to those who presented at the UAI 2000 Workshop on Knowledge-Data Fusion: it is open to everyone who has an interest in this topic. Please direct any enquiries to Richard Dybowski: rdybowski@btinternet.com Schedule -------------- Paper submission deadline: July 1, 2001 <<<<<<<<< New deadline Authors' notification of decisions: October 1, 2001 Final revised papers due: January 15, 2002 ------------------------------ From: Ali Zalzala Subject: [CEC2002] First Call for Papers Date: Thu, 14 Jun 2001 9:50:39 +0100 CALL FOR PAPERS 2002 Congress on Evolutionary Computation May 12-17, 2002 Hilton Hawaiian Village, Honolulu, HI Held as part of the WCCI World Congress on Computational Intelligence (http://www.wcci2002.org) The annual Congress on Evolutionary Computation (CEC) is one of the premier international conferences in the field. It covers all topics in evolutionary computation: from combinatorial to numerical optimization, from supervised to unsupervised learning, from co-evolution to collective behaviors, from evolutionary design to evolvable hardware, from molecular to quantum computing, from ant colony to artificial ecology, etc. The emphasis of the Congress will be on original theories and novel applications of evolutionary computation techniques. The Congress welcomes paper submissions from researchers, practitioners, and students worldwide. The 2002 Congress will be held in conjunction with the International Joint Conference on Neural Networks (IJCNN) and the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) as part of the World Congress on Computational Intelligence (WCCI). Crossfertilization of the three fields will be strongly encouraged. The Congress will feature keynote speeches and tutorials by world-leading researchers. It also will include a number of special sessions and workshops on the latest hot topics. Your registration admits you to all events and includes the World Congress proceedings and banquet. The deadline for submissions is 15 October 2001. Look for more details on paper submission and conference registration coming soon at http://www.wcci2002.org. CEC is jointly supported by the IEEE Neural Networks Council, the Evolutionary Programming Society, and the Institution of Electrical Engineers. ------------------------------ From: Luis Torgo Subject: Workshop on Artificial Intelligence for Financial Time Series Analysis Date: Tue, 19 Jun 2001 16:30:11 +0100 Call for Papers Artificial Intelligence for Financial Time Series Analysis http://www.ncc.up.pt/~ltorgo/AIFTSA/ A Workshop of the 10th Portuguese Conference on Artificial Intelligence (EPIA'01) 17-20 December, Porto, Portugal Papers due : 13 July 01 The 10th EPIA will continue the tradition of previous Portuguese AI conferences and will be organized under the auspices of the Portuguese Association for Artificial Intelligence (APPIA). The conference will maintain its international character and continue to provide a forum for presenting and discussing research on different aspects of AI. The conference language is English and selected papers will be published by Springer-Verlag. In this edition of EPIA the conference chairs have decided to strengthen the role of thematic workshops in order to promote discussion among participants. The workshops will not be just satellite events, but rather form an integral part of the conference. Certain sessions of the workshops (e.g. invited speakers) will, at the same time, form part of the main conference. Workshop papers of high quality will be selected for publication in the main volume of conference proceedings. This workshop on Artificial Intelligence for Financial Time Series Analysis aims at proving a discussion forum for researchers interested in the application of AI techniques in the topic of Financial Time Series Analysis. AI-based data analysis techniques such as symbolic machine learning, neural networks and others have being increasingly used by financial management institutions. The exponential growth of financial information available through the Web further stresses the need for automatic knowledge extraction using techniques that are able to use this information to increase the accuracy of market forecasts. Topics of interest to this workshop include, but are not limited to: - Trading and forecasting methods - Symbolic learning methods for time series modeling - Neural networks for time series modeling - Data pre-processing techniques for time series modeling - Automatic financial information extraction from the Web # Important Dates: Submission Deadline: 13 July 01 Acceptance Notice: 15 September 01 Camera Ready Copies: 01 October 01 # Submission of Papers: Authors should submit their papers by electronic mail to the workshop chair (email), as postscript (eventually gzipped) or pdf files. Hard copy submission is also possible, by sending 3 copies of the manuscripts to the address of the workshop organization (see bellow). To be considered for publication in the conference proceedings edited by Springer, papers must not have been previously published or simultaneously submitted for publication elsewhere. Submissions must not exceed 15 pages, including title page, figures, and references. The title page must contain: title and authors; physical and e-mail addresses; an abstract of no more than 200 words; a list of keywords. Papers should be formatted according to Springer's LNCS format, details of which can be obtained from http:/www.springer.de/comp/lncs/authors.html. ------------------------------ Jobs ------------------------------ From: "Chen, Francine " Subject: Research Position at Xerox PARC Date: Mon, 12 Mar 2001 11:54:22 PST The Quantitative Content Analysis Area (QCA) at Xerox PARC is seeking researchers/developers who have a strong background (Ph.D or M.S.) in applying statistical machine learning or pattern recognition techniques to information access tasks, such as organization and mining of documents and document collections. We have developed methods in areas such as summarization, genre identification, use of multi-modal information in browsing, and topic identification. Our current focus is on interactive methods to extract information from large document collections and to restructure it based on the needs of individual users. We are building up a team composed of computer scientists and engineers, with specialists in natural language and machine learning. To be successful, candidates need to have strong programming skills (Java or C/C++), be able to develop algorithms as well as novel applications and work well with others on both foundational research and on more application-oriented research projects in a multidisciplinary (and multinational) setting. Experience and qualifications o PhD/M.S. in computer science or related fields with a strong background in machine learning, pattern recognition, probability or statistics with strong programming skills (Java or C/C++) o Experience or interest in information access o Interest or experience in quantitative natural language analysis, image analysis and/or user interfaces a plus o Experience in working with large corpora and net applications is a plus To apply, please submit your resume with a list of publications and references via email to istlhiring@parc.xerox.com, and identify the position in the subject line as "Quantitative Content Analysis Area (QCA)". Xerox is an Equal Employment Opportunity company committed to the principles of workforce diversity. ------------------------------ From: Kevin Korb Subject: Research Fellow in Computational Data Analysis and Modelling (2 positions) Date: Tue, 27 Mar 2001 15:34:46 +1000 Research Fellow in Computational Data Analysis and Modelling (2 positions) The Monash Data Mining Centre at the Clayton campus of Monash University seeks two Research Fellows in Computational Data Analysis. Applicants should have a PhD in a relevant area, such as Computational Data Analysis, Data Mining, Machine Learning, Econometrics, Bioinformatics or Statistics. Appointees will participate in the research activities of the Centre, including liaising and collaborating with industrial research partners. Experience in an industrial environment is desirable. A computer programming background is required. Experience in one or more of information theory, Bayesian statistics and Bayesian networks will also be an advantage. Salary: Depending on experience in the range Research Fellow Level A or Level B (AU$44,999 through AU$60,382) on a 12-month contract with possibility of extension. Positions available immediately. Applications and inquiries to Leeanne Evans: School of Computer Science and Software Engineering, P.O. Box 26, Monash University, Victoria 3800, Australia. Phone (03)9905-5200. Email leeanne@csse.monash.edu.au ------------------------------ From: Gunter Grieser Subject: Research Positions available Date: Thu, 05 Apr 2001 16:45:43 +0200 The Institute of Intellectics at the Technical University of Darmstadt, Germany, offers two ============================= PhD and PostDoc Positions ============================= for our research projects LExIKON und DaMiT. LExIKON is a research and development project focussing an innovative approach to knowledge extraction from the Internet. The peculiarity of LExIKON is to invoke inductive learning techniques on different levels. By its way of integrating inductive inference into knowledge extraction from the Internet, LExIKON is distinguished from all competing projects throughout the world. The LExIKON research deals with the development of new learning algorithms, with their study and with proofs of formal results about the algorithms' power and limitations. Those algorithms are prototypically implemented and practically evaluated within the LExIKON project. LExIKON puts emphasis on the development of a core system named the Intelligent Extraction Unit (IEU). Embedding LExIKON's IEU into a conventional search engine may result into a breakthrough to the next generation of those systems. The project partners are three german universities, the German Research Center for Artificial Intelligence, two software houses and a bank. DaMiT aims at the development of a tutoring system for data mining. Its pecularity is the fact that the topic and the location of teaching coincide: extraction of information from huge and distributed data bases as well as from the internet cannot be studied more realistic than in the internet itselfes. Within the projekt DaMiT, the fundamentals of machine learning, ranging from inductive inference to knowledge discovery and data mining, will be elaborated, will be prepared for teaching in the internet and will be integrated in a tutoring system. Within this system, algorithms as well as complete systems for data mining and knowledge discovery are accessible. Thus, the students can probe their knowledge practically. The project consortium consists of 10 german universities. keywords artificial intelligence, machine learning, knowledge extraction, data mining start promptly possible project descriptions http://lexikon.dfki.de http://damit.dfki.de contact and further information Gunter Grieser, Tel. +49+6151+166634, grieser@informatik.tu-darmstadt.de ------------------------------ From: Daphne Koller Subject: Postdoc opportunity Date: Sun, 8 Apr 2001 16:10:22 -0700 CALL FOR APPLICATIONS POSTDOCTORAL RESEARCH ASSOCIATE Probabilistic methods Topics of particular interest include: * Probabilistic graphical models (e.g., Bayesian networks) * Statistical learning * Decision making under uncertainty * Reinforcement learning * Bioinformatics The postdoctoral research associate will be part of Daphne Koller's group at Stanford University. The group currently consists of nine PhD students, a postdoctoral research associate, and several masters students and undergraduates. In general, Stanford offers a lively and exciting environment, with outstanding students and leading researchers in a variety of areas and departments. The successful applicant will be expected to conduct theoretical and applied research in one or more of these areas, and to be willing to interact with the group on projects in other areas. Applicants should * have a solid background in one or more of the areas above * have good scientific skills * be willing to take an active role in the research group. Applicants should EMAIL a CV, the names and email addresses of three references, and a short description of their research interests and goals as a postdoc (< 500 words) to Daphne Koller (koller@cs.stanford.edu). All materials should be sent in ASCII text, postscript or PDF format. The selection process will begin immediately, so applications should be sent as soon as possible. ------------------------------ From: Luc De Raedt Subject: Re: Job Opening Date: Wed, 11 Apr 2001 22:42:30 +0100 The Machine Learning and Natural Language Processing Lab of the Albert-Ludwig-University Freiburg, Germany, is involved in the ESPRIT IST FET project cInQ (Consortium on Inductive Query Languages). This project is expected to start in May 2001 and to run for three years. The topic of the project is Inductive Query Languages. These are database mining languages that allow to query patterns in databases. In this way they support not only the retrieval of information that resides in the database but also to discover the regularities that are implicit in the data. For this project, the Machine Learning and Natural Language Lab seeks a research assistant (level Bat IIa) at the pre-doctoral or post-doctoral level. The ideal candidate has a degree in computer science, with a specialization in databases, data mining and logic programming. While German language capabilities are not required at the time of employment, it is expected and highly recommended that the successful candidate is open towards acquiring some basic German communication skills. In case of equal qualifications candidates with disabilities will be prefered. The University is striving for an increase of the proportion of female employees and expressly encourages women to apply. The Albert-Ludwigs-University Freiburg is looking back on more than 500 years of history. The Institute for Computer Science is part of the newly founded Faculty for Applied Sciences. The city of Freiburg is located at the foot of the Black Forest in south-western Germany in close proximity of the French Alsace as well as north-western Switzerland, and offers high living standards and ample opportunities for recreational activities. Interested candidates should contact Prof. Dr. Luc De Raedt, preferably by email (deraedt@informatik.uni-freiburg.de), see also http://www.informatik.uni-freiburg.de/~ml/. ------------------------------ From: Russ Greiner Subject: Call for Applications: PostDoctoral Research Scientists Date: Fri, 13 Apr 2001 19:15:52 -0600 POSTDOCTORAL RESEARCH SCIENTISTS Call for Applications Bioinformatics - Query Answering - Game Playing - Adaptive Agents Machine Learning - Probabilistic Modelling - Decision Support Just got your PhD and want to focus on pure curiosity-driven research before jumping into the tenure-track pressure cooker? We are looking for one or more postdoctoral research scientists (PDRS), to help us work on theoretical and applied research in various specific research projects -- related to the topics listed above and with the individual researchers below, in collaboration with various research-friendly companies, including BioTools, Chenomx, Electronic Arts, CELcorp, net-linx, Syncrude, ... These PostDoc positions improve on most positions as... * The salary will be competitive with tenure-track positions. * You will also be allowed/expected to spend 50% of your time on your own curiousity-driven agenda -- we hope in collaboration with various members of our faculty; see http://www.cs.ualberta.ca/~ai. You will be part of a team that has recently emerged as one of the strongest AI groups anywhere, with a number of world-class professors that include editors-in-chief of major journals, AAAI Fellows, Steacie Fellows, McCalla Fellows ... And we are continuing to grow and improve. Moreover, our department is known for its collegiality. You will also help us show off our group in 2002, when we will host AAAI'02 http://aaai.org KDD'02 http://www.acm.org/sigkdd ISMB'02 http://www.iscb.org Applicants should * have a solid background in one or more of the areas described above * have good scientific skills * be good at writing software to implement and evaluate algorithms Successful applicants will have the opportunity to do sessional teaching in the department of Computing Science. Applicants should EMAIL a CV, the email addresses of 3 references, and a short description of their research interests and goals as a postdoc (ascii format, < 500 words) to Russ Greiner (greiner@cs.ualberta.ca) You are encouraged to *also* post additional information on http://www.cs.ualberta.ca/jobs/postdoc.html We are very flexible with time commitments; applicants should indicate how long they would like to remain as a PDRS -- typical stay is between 1 and 3 years. We are an equal opportunity employer, eagerly seeking applicants from Canada or any other country. For more information, see http://www.cs.ualberta.ca/~greiner/PostDoc.html ------------------------------ From: Noel Sharkey Subject: JOB in Evolutionary Collective Robotics Date: Mon, 28 May 2001 11:24:23 +0100 (BST) The following job will shortly be advertised in the press and we need someone ASAP - please excuse multiple postings. Research Associate/Assistant in Evolutionary Collective Robotics This is an exciting opportunity to join a team working on high profile projects at the Creative Robotics Unit at Magna, directed by Prof. Noel Sharkey. The recently opened unit is a joint project between the University of Sheffield and the new Magna science adventure centre (over 100K visitors in its first month). There are two main projects at present with more to follow soon: (i) a large scale predator and prey study in a ``self-sustaining'' ecology (featured on BBC's Tomorrow's World) and (ii) an investigation of flocking and swarming with large autonomous aerial robots. We are currently looking for an additional researcher for the predator/prey project. Proficiency in C programming is required. Salary according to age and experience. Our brief is produce leading edge robotics research that is both transparent and intrinsically interesting to the general public. For further information please contact m.kus@dcs.shef.ac.uk. Please send an statement of interest and a CV and we will get back to you quickly about an application. ------------------------------ From: Technopros Subject: : Biostatistician Job Opening in San Francisco, California Date: Wed, 30 May 2001 13:47:59 -0700 Technopros is looking for dedicated professionals to work as contract Statistical Consultants. If you are a highly skilled Statistician, Statistical Analysts or SAS Programmer who wants to apply your expertise, email your resume to Technopros: We have openings for: JOB TITLE: Biostatistician/SAS LOCATION: San Francisco, CA JOB TYPE: Contract and Direct openings. Rate : Market Rate Summary of Duties: You will be providing statistical and statistical programming support to clinical trials or pre-clinical trials. Working knowledge of medical terminology and good general communication skills is necessary. My client is looking for someone who willd possess a MS or Ph.D in statistics, Epidemiology, or closely related field. Must have knowledge of SAS. Experience in support of clinical trials will be helpful. Familiarity with the Survival Analysis process using SAS is desired. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ CLINICAL STATISTICIAN: With demonstrated clinical SAS experience. Develop clinical analysis plans. Knowledge of clinical protocols and statistical reports required. Good written and verbal communication skills highly desired. MS or Ph.D. degree in statistics required. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ SENIOR BIOSTATISTICAN: Perform clinical data analyses, interpret results for clinical reports and New Drug Applications. Design and implement clinical protocols. Experience in clinical data analysis using SAS. MS or Ph.D. degree in statistics required. ------------------------------ From: Luca Maria Gambardella Subject: IDSIA: Two Post DOC Positions in Robotics, Swarm Intelligence and Machine learning Date: Mon, 11 Jun 2001 12:53:16 +0200 ============================================================================== Job Opening in Robotics, Swarm Intelligence, Machine Learning and Simulation ============================================================================== TWO POST DOC POSITIONS for 3 years funded by the Future and Emerging Technologies (FET) program of the Commission of the European Community is open for applications. IDSIA, http://www.idsia.ch Istituto Dalle Molle di Studi sull'Intelligenza Artificiale, Galleria 2, 6928 Manno-Lugano, Switzerland APPLICATION DEADLINE: July 30th 2001 STARTING: October 2001: We are looking for two Post Doctoral candidates to work on the new European Project SWARM-BOTS starting October 2001. SWARM-BOTS is about the design and implementation of self-organising and self assembling artifacts called swarm-bots. The approach is inspired by recent studies in swarm intelligence, i.e., by studies of the self-organising and self-assembling capabilities shown by social insects and other animal societies. The main scientific goal of the project is a better understanding of swarm intelligence principles and of the use of these principles in engineering, while the main tangible goal is the demonstration of the validity of the approach followed by means of the construction of at least one such artifact. The expected results are therefore the further development of the swarm intelligence discipline and the design and construction of a first example of swarm-bots, that is, an artifact composed of a number of simpler robots capable of self-assembling and self-organising to adapt to its environment. The project will last 36 months and will see the combined effort of scientists from four European laboratories (IRIDIA Bruxelles, IDSIA Lugano, EPFL Lausanne, CNR-IP Rome) ====================== CONTACT INFORMATION ===================== If you wish to apply, please send (i) Detailed curriculum vitae (ii) List of three references (and their email addresses) (iii) Transcripts of undergraduate and graduate (if applicable) studies (iv) Concise statement of your research interests (two pages max). Candidates are also encouraged to submit their scores in the Graduate Record Examination (GRE) general test (if available). Applications can also be submitted electronically (in plain ASCII or postscript format) to mailto:luca@idsia.ch. Please connect "SWB2001PD" with your first and last name in the message subject. Please send all documents to: Luca Maria Gambardella IDSIA Galleria 2 6928 Manno-Lugano Switzerland Phone : +41 91 - 610 8663 Fax : +41 91 - 610 8661 Secretary: +41 91 - 6108660 mailto:luca@idsia.ch http://www.idsia.ch/luca ------------------------------ Other ------------------------------ From: "Lawrence, Joanna" Subject: NEW BOOK! by Lorenzo Magnani Date: Tue, 13 Mar 2001 16:08:23 -0000 Kluwer Academic/Plenum Publishers London Abduction, Reason, and Science Processes of Discovery and Explanation by Lorenzo Magnani University of Pavia, Pavia, Italy and Georgia Institute of Technology, Atlanta, Georgia, USA 0-306-46514-0/March 2001/224pp Euro 88.50/ USD 85/ GBP 58.75 More than a hundred years ago, the great American philosopher Charles Sanders Peirce coined the term "abduction" to refer to inference that involves the generation and evaluation of explanatory hypotheses. The study of abductive inference was slow to develop, as logicians concentrated on deductive logic and on inductive logic based on formal calculi such as probability theory. In recent decades, however, there has been renewed interest in abductive inference, from two primary sources. Philosophers of science have recognized the importance of abduction in the discovery and evaluation of scientific theories, and researchers in artificial intelligence have realized that abduction is a key part of medical diagnosis and other tasks that require finding explanations. Psychologists have been slow to adopt the terms "abduction" and "abductive inference", but have been showing increasing concerns with causal and explanatory reasoning Thus abduction is now a key topic of research in cognitive science, the interdisciplinary study of mind and intelligence. This new book Abduction, Reason, and Science contributes to this research in several interesting ways. First, it ties together the concerns of philosophers of science and AI researchers, showing, for example, the connections between scientific thinking and medical expert systems. Second, it lays out a useful general framework for discussion of a variety of kinds of abduction. Third, it develops important ideas about aspects of abductive reasoning that have been relatively neglected in cognitive science, including the use of visual and temporal representations and the role of abduction in the withdrawal of hypotheses. The author has provided a valuable contribution to the renaissance of research on explanatory reasoning. Contents Hypothesis Generation ? Theoretical Abduction ? Manipulative Abduction ? Diagnostic Reasoning ? Visual and Temporal Abduction ? Governing Inconsistencies ? Hypothesis Withdrawal in Science ? To Order this Book please contact: Kluwer Academic Publishers Order Department P.O. Box 322 3300 AH Dordrecht The Netherlands *: +31 78 6392 392 Fax: +31 78 6546 474 E-mail: Orderdept@wkap.nl Customer service dept: services@wkap.nl Or for customers in USA, Canada, Mexico and Latin America: Kluwer Academic Publishers Order Department P.O. Box 358 Accord Station Hingham, MA 02018-0358, U.S.A. *: +1 781 871 6600 Fax: +1 781 871 6528 Customer service dept: kluwer@wkap.com ------------------------------ From: Tom Fawcett Subject: Fraud detection bibliography available Date: Thu, 19 Apr 2001 13:26:16 -0700 I have cleaned up and released publicly a bibliography on fraud detection. It concentrates primarily on data mining and machine learning approaches for automatically detecting fraud from data. There are some papers on computer intrusion and cellular phone fraud as well. The nice web interface is here: http://liinwww.ira.uka.de/bibliography/Ai/fraud.detection.html The raw (BibTex) file is here: http://www.purl.org/net/tfawcett/bibs/fraud-public.bib.gz I'm no longer actively working in this area, but I'm trying to keep up with the field so I'm maintaining the bibliography. Any corrections and additions are welcome. Tom Fawcett Hewlett-Packard Laboratories Palo Alto, CA ------------------------------ From: Paolo Frasconi Subject: Special issue on connectionist models for learning in structured domains Date: Fri, 20 Apr 2001 13:07:21 +0200 The members of this list may be interested in the most recent issue of the IEEE Transactions on Knowledge and Data Engineering which is a Special Issue on Connectionist Models for Learning in Structured Domains. IEEE Transactions on Knowledge and Data Engineering Vol. 13, No. 2, March/April 2001 SPECIAL SECTION ON CONNECTIONIST MODELS FOR LEARNING IN STRUCTURED DOMAINS Abstracts can be found at http://www.dsi.unifi.it/neural/tkde-datas.html Full text is available to subscribers from the IEEE TKDE home page http://computer.org/tkde/index.htm Guest Editorial Introduction to the Special Section P. Frasconi, M. Gori, and A. Sperduti Simple Strategies to Encode Tree Automata in Sigmoid Recursive Neural Networks R.C. Carrasco and M.L. Forcada Integrating Linguistic Primitives in Learning Context-Dependent Representation S.W.K. Chan Symbolic vs. Connectionist Learning: An Experimental Comparison in a Structured Domain P. Foggia, R. Genna, and M. Vento Generalization Ability of Folding Networks B. Hammer Hierarchical Growing Cell Structures: TreeGCS V.J. Hodge and J. Austin Incremental Syntactic Parsing of Natural Language Corpora with Simple Synchrony Networks P.C.R. Lane and J.B. Henderson Learning Distributed Representations of Concepts Using Linear Relational Embedding A. Paccanaro and G.E. Hinton Clustering and Classification in Structured Data Domains Using Fuzzy Lattice Neurocomputing (FLN) V. Petridis and V.G. Kaburlasos Representation and Processing of Structures with Binary Sparse Distributed Codes D.A. Rachkovskij [Sorry, I can provide no hardcopies - for electronic copies, please contact the authors directly]. ------------------------------ From: Steve Minton Subject: JAIR ML-related articles Date: Sun, 22 Apr 2001 13:17:41 -0700 Readers of this list may be interested in the following machine learning articles that were published in the last two volumes in JAIR (www.jair.org): Baxter, J. (2000) "A Model of Inductive Bias Learning", Volume 12, pages 149-198. Walker, M.A. (2000) "An Application of Reinforcement Learning to Dialogue Strategy Selection in a Spoken Dialogue System for Email", Volume 12, pages 387-416. Gordon, D.F. (2000) "Asimovian Adaptive Agents", Volume 13, pages 95-153. Dietterich, T.G. (2000) "Hierarchical Reinforcement Learning with the MAXQ Value Function Decomposition", Volume 13, pages 227-303. - Steven Minton JAIR Managing Editor ------------------------------ From: rsun@cecs.missouri.edu Subject: special issue on multi-agent learning Date: Thu, 3 May 2001 10:59:23 -0500 COGNITIVE SYSTEMS RESEARCH Special Issue -- Multi-disciplinary studies of multi-agent learning -- special issue editor: Ron Sun (rsun@cecs.missouri.edu) Cognitive Systems Research Volume 2, Issue 1, April 2001 Ron Sun Editorial: Individual action and collective function: From sociology to multi-agent learning 1-3 (PDF 42.3 Kb) Cristiano Castelfranchi The theory of social functions: challenges for computational social science and multi-agent learning 5-38 (PDF 425.2 Kb) Tom R. Burns and Anna Gomolińska Socio-cognitive mechanisms of belief change - Applications of generalized game theory to belief revision, social fabrication, and self-fulfilling prophesy 39-54 (PDF 139.5 Kb) Michael L. Littman Value-function reinforcement learning in Markov games (PDF 108 Kb) 55-66 Junling Hu and Michael P. Weliman Learning about other agents in a dynamic multiagent system (PDF 515.3 Kb) 67-79 Maja J. Mataric Learning in behavior-based multi-robot systems: policies, models, and other agents 81-93 (PDF 295.6 Kb) Please see: http://www.elsevier.nl/gej-ng/10/15/16/58/25/show/toc.htt or http://www.cecs.missouri.edu/~rsun/journal.html for abstracts and full papers in PDF ------------------------------ From: David Maxwell Chickering Subject: WinMine Toolkit version 1.0 Date: Thu, 17 May 2001 13:44:43 -0700 I am pleased to announce that the WinMine Toolkit version 1.0, developed by the Machine Learning and Applied Statistics group in Microsoft Research, is now available for academic use. This release includes tools for - Learning Bayesian networks, dependency networks, and decision trees from data - Evaluating the predictive accuracy of learned models - Viewing and browsing learned models This release runs under the Windows NT/2000 operating systems. It includes command-line executables that facilitate scripting of experiments. The toolkit uses XML formats for both data and models. To learn more about the features of this release or to download it, please go to http://research.microsoft.com/~dmax/WinMine/tooldoc.htm Max Chickering ------------------------------ End of ML-LIST Digest Vol 13, No. 3 ***********************************