Received: from ics.uci.edu by Paris.ics.uci.edu id aa04603; 21 Jan 92 12:38 PST Received: from ics.uci.edu by q2.ics.uci.edu id aa18044; 21 Jan 92 12:38 PST To: ML-LIST: ; Subject: Machine Learning List: Vol. 4 No. 1 Reply-to: ml@ics.uci.edu Date: Tue, 21 Jan 92 12:32:26 -0800 From: Michael Pazzani Message-ID: <9201211238.aa18044@q2.ics.uci.edu> Machine Learning List: Vol. 4 No. 1 Tuesday, Jan 21, 1992 Contents: Learning And Vision AAAI-92 Workshop on Approximation and Abstraction AAAI-92 Workshop on Constraining Learning with Prior Knowledge The Second International Workshop on Inductive Logic Programming The Machine Learning List is moderated. Contributions should be relevant to the scientific study of machine learning. Mail contributions to ml@ics.uci.edu. Mail requests to be added or deleted to ml-request@ics.uci.edu. Back issues may be FTP'd from ics.uci.edu in pub/ml-list/V/ or N.Z where X and N are the volume and number of the issue; ID: anonymous PASSWORD: ------------------------------ Date: Tue, 7 Jan 92 00:23:53 CST From: "Douglas H. Fisher" Subject: learning and vision See the Dec 1991 IEEE PAMI for instructions on submission to a special issue on `learning and computer vision.' ------------------------------ From: ellman@cs.rutgers.EDU Date: Mon, 13 Jan 92 14:40:07 EST Subject: Workshop on Approximation and Abstraction Approximation and Abstraction of Computational Theories AAAI-92 Workshop, San Jose, California, July 1992 Thomas Ellman (Chair) (Rutgers University) ellman@cs.rutgers.edu Brian Falkenhainer (Xerox PARC) falkenhainer.pa@xerox.com Fausto Giunchiglia (IRST) fausto@irst.it Richard Keller (NASA Ames Research Center) keller@ptolemy.arc.nasa.gov Craig Knoblock (USC Information Sciences Institute) knoblock@isi.edu Devika Subramanian (Cornell University) devika@cs.cornell.edu Toby Walsh (University of Edinburgh) T.Walsh@edinburgh.ac.uk 1 Topic of the Workshop Approximations and abstractions are used frequently to overcome computational intractability in knowledge-based systems. In planning, scheduling and design tasks, for example, approximations and abstractions diminish the combinatorial costs of searching large spaces. In simulation, diagnosis and monitoring tasks, approximations and abstractions diminish the costs of tracking interactions among large numbers of variables. Current practice usually requires human experts to provide approximations or abstractions that are suitable to the problem at hand. A number of investigators is attempting to remove this burden from humans. One line of investigation is aimed at automating the synthesis problem, i.e., given a complete, correct but intractable domain theory, construct an approximate or abstract version of the theory. A second line of investigation is directed at the selection problem, i.e., given a set of different approximate or abstract domain theories, select one that is most appropriate to the problem at hand. The workshop is intended to examine both the synthesis problem and the selection problem. 2 Objectives of the Workshop Although a growing number of investigators is studying approximation and abstraction of computational theories, the field has yet to adopt a shared framework for discussing various approaches and research issues. The workshop is intended to promote such a shared framework. It will introduce participants to research on approximation and abstraction carried out in fields other than their own specialties. It will enable participants to compare goals, techniques, vocabularies and paradigms. It will encourage participants to identify important research issues and engineering hurdles. Finally, it will facilitate the process of setting up collaborative research projects. 3 Format and Intended Audience The need for good approximations and abstractions cuts across all areas of artificial intelligence. The workshop is therefore aimed at investigators from a variety of areas within the AI community, including machine learning, qualitative physics, planning, automatic programming and logic, among others. It is also intended to include people focused on AI applications in areas such as scheduling, design, simulation, databases, mechanical engineering, medicine and biology. Approximately forty to fifty people will be invited to attend. The workshop will include a limited number of formal presentations as well as a panel discussion. The format will promote interaction and informal discussion among participants. 4 Submission Requirements Persons wishing to attend the workshop should submit five copies of a 1 - 2 page research summary including a list of relevant publications, along with a phone number and an electronic mail address if possible. Persons wishing to make presentations at the workshop should submit five copies of a short paper or extended abstract, in addition to the research summary. All submissions must be received by March 13, 1992 and must be made in the form of paper copies. Electronic submissions will not be accepted. Notification of acceptance or rejection will be mailed to applicants by April 3, 1992. Camera ready copies of papers accepted for inclusion in the working notes of the workshop will be due on April 17, 1992. In order to facilitate communication among participants, authors are encouraged to address the following questions in their papers or research summaries: What types of computational theories are you investigating? How are the theories represented? What types of approximations or abstractions are you investigating? What purpose do they serve? What tradeoffs do they incorporate? How are they synthesized or selected? What knowledge, criteria and mechanisms are used to find good approximations or abstractions? What aspects of the synthesis or selection process appear useful and feasible to automate? What hurdles must be overcome in order to apply your approach to important problems? What are good research goals and challenge problems for the field? 5 Submission Address Thomas Ellman Department of Computer Science Rutgers University Hill Center, Busch Campus New Brunswick, NJ 08903 Phone: (908) 932-4184 FAX: (908) 932-5530 Email: ellman@cs.rutgers.edu ------------------------------ Date: Mon, 20 Jan 92 11:41:24 -0800 From: Marie desJardins Subject: AAAI-92 workshop on Constraining Learning with Prior Knowledge CALL FOR PARTICIPATION: AAAI-92 Workshop on Constraining Learning with Prior Knowledge DESCRIPTION OF WORKSHOP Scaling up machine learning techniques to large domains will not be feasible unless we can find ways to reduce the complexity of the learning task. One of the primary ways this can be done is by constraining learning using domain knowledge. By bringing specific knowledge to bear, the complexity of a learning problem can be greatly reduced. Furthermore, ignoring available knowledge may cause a system to form incorrect beliefs. Explanation-based learning techniques use a complete and correct domain theory to provide an extremely strong constraint on learning. In this workshop, we will be exploring how other forms of knowledge can be used to constrain learning to a lesser degree. The objective of this workshop is to bring together researchers from a variety of fields to discuss the problem of using explicit representations of prior knowledge to constrain learning. Specific research areas include: 1. How can prior knowledge be used to constrain, or bias, the learning problem? (E.g., using a half-order theory as in Meta-DENDRAL, selecting a feature set, or suggesting relevant experiments.) 2. How can the bias be represented so that it may be integrated into a general learning model? (E.g., as search control heuristics or as linguistic templates.) 3. What form does the prior knowledge take? (E.g., monotonicity constraints, partial domain theories, or probability distribution information.) 4. How can techniques for using different types of knowledge be integrated into a single learning system? 5. Where does the knowledge come from? (E.g., from prior learning or expert advice.) This is not an exhaustive list of topics of interest. In particular, we hope to encourage a broad interpretation of the term ``prior knowledge.'' For example, knowledge about the computational complexity of the concept to be learned and of the learning process itself, and resource limitations of the learning system, can be treated as prior knowledge; therefore, research on resource-bounded learning methods that use explicit models of time and space requirements is relevant to the workshop. Many existing systems embody knowledge that is treated as an implicit assumption, such as the initial weights in a connectionist system. We encourage submission of theoretical or empirical work that explicitly considers the sources and effects of these initial assumptions. We are especially interested in views on this problem from other research areas, including but not limited to: - Cognitive and developmental psychology. - Knowledge representation. - Computational learning theory. - Neural networks. - Heuristic search. - Constraint-based reasoning. - Qualitative reasoning. We are not looking for lists of constraints for specific problem areas. Rather, the focus is on innovative approaches to the research questions enumerated above that will lead to domain-independent ways to incorporate domain-specific knowledge into the learning process. In order to encourage an open forum for discussion, the workshop will be limited to approximately 30 to 40 participants. Preference will be given to those who have done research on explicitly using prior knowledge to constrain learning. However, we will also invite researchers who have done work in related fields with demonstrable relevance to the topic of the workshop, and some graduate students who have an interest in the field. Please feel free to contact any of the program committee members to discuss the relevance of your research to the workshop. The workshop will include ten to twelve technical presentations, an invited talk by Bruce Buchanan, and a wrap-up discussion session at the end of the day. If there are a large number of high-quality submissions, we may consider an additional poster session. Those who wish to attend the workshop should send a two- or three-page research summary following the submission guidelines below. The summary should describe your research interests, and discuss their connection to the workshop topic. Those who wish to present a paper should send a paper of no more than 4000 words, again following the guidelines below. You may, if you wish, also submit a research summary which discusses your research program in more breadth than would be appropriate in a technical paper. Submission guidelines: e-mail submissions are preferred, to marie@erg.sri.com. Electronic submissions must be in ``standalone'' LaTeX format (i.e., no included PostScript files). If e-mail submission is not possible, please send four hard copies to the workshop chair (address is given below). All submissions must reach the chair by March 13. Submissions will be reviewed by at least two reviewers. Notification of acceptance or rejection of papers, and invitations to attend the workshop, will be sent by April 3. The workshop notes will include presented papers (ten-page limit) and one-page research summaries from all participants. The papers and summaries will be due, in camera-ready or electronic form, by April 17. WORKSHOP CHAIR: Marie desJardins SRI International 333 Ravenswood Ave. Menlo Park CA 94025 marie@erg.sri.com (415) 859-6323 PROGRAM COMMITTEE: William Cohen, AT&T Bell Laboratories (wcohen@research.att.com) Marie desJardins, SRI International (marie@erg.sri.com) Haym Hirsh, Rutgers University (hirsh@pei.rutgers.edu) Doug Medin, University of Michigan (Doug_Medin@um.cc.umich.edu) ------------------------------ Subject: Int. Workshop on Inductive Logic Programming (ILP92) Date: 21 Jan 92 02:59:25 GMT From: ueda@icot31.icot.or.jp (Ueda Kazunori) --- First Announcement and Call for Participation --- The Second International Workshop on Inductive Logic Programming (ILP92) June 6-7, 1992 ICOT, Tokyo, Japan in conjunction with International Conference on Fifth Generation Computer Systems 1992 June 1-5, 1992 This workshop is the second in a series of International Workshops on Inductive Logic Programing. The workshop will bring together an international group of researchers in the field. Inductive Logic Programming is an emerging research area, spawned by Machine Learning and Logic Programming. While the influence of Logic Programming has encouraged the development of strong theoretical foundations, this new area is inheriting its experimental orientation from Machine Learning. To restrict the workshop to a manageable size, participation is on an invitational basis. However, invitations could be extended slightly if the demand exists. (Please contact the Program Chair.) Participants are welcome either to present new results or simply to take part in the discussions. Papers are encouraged in, though not restricted to, the following areas. [Theory.] Papers should either (1) prove new results concerning programs which use inductive learning to construct first or higher order logic descriptions or (2) discuss the relationship of Inductive Logic Programming to other theoretical areas such as Non-Monotonic Logic or Abductive Reasoning. Learnability results and theoretical investigations of predicate invention are especially welcome. [Implementation.] Details of inductive algorithms. Time complexity results should be included. [Experimentation.] Experimental results should be tabulated with appropriate statistics. Sufficient details should be included to allow reproduction of results. Comparative studies of different algorithms running on the same examples, using the same background knowledge, are especially welcome. The workshop will immediately follow the International Conference on Fifth Generation Computer Systems (FGCS92) which will be held in Tokyo (Tokyo Prince Hotel), June 1-5, 1992. Attendees are thus encouraged to take part in both ILP92 and the larger FGCS92 conference (contact: fgcs92@icot.or.jp, fax:+81-3-3456-1618). Participants must find their own funds for travel. ORGANIZATION Program Chair: Stephen Muggleton Turing Institute George House 36 North Hanover Street Glasgow, G1 2AD, U.K. e-mail: steve@turing.ac.uk fax: +44-41-552-2985, tel: +44-41-552-6400 Local Chair: Koichi Furukawa Institute for New Generation Computer Technology (ICOT) Mita Kokusai Bldg. 21F 4-28 Mita 1-chome, Minato-ku Tokyo 108, Japan e-mail: furukawa@icot.or.jp fax: +81-3-3456-1618, tel: +81-3-3456-3195 PAPER SUBMISSIONS Printed papers to be included in the proceedings of the workshop must be received by the program chair no later than February 16, 1992. To ensure that papers in the proceedings are readable, only hard-copy papers will be accepted, not papers sent by email or fax. Papers received after the deadline will not be included in the proceedings. ------------------------------ END of ML-LIST 4.1