From jq@lirmm.lirmm.fr Mon Oct 10 17:40:59 1994 Received: from [193.49.104.48] ([193.49.104.48]) by lirmm.lirmm.fr (8.6.9/8.6.4) with SMTP id RAA02662; Mon, 10 Oct 1994 17:40:52 +0100 Date: Mon, 10 Oct 1994 17:40:52 +0100 Message-Id: <199410101640.RAA02662@lirmm.lirmm.fr> X-Sender: jq@lirmm.lirmm.fr Mime-Version: 1.0 Content-Type: text/plain; charset="us-ascii" X-Mailer: Eudora F1.4 To: gascuel, hr, reitz, js, mephu, pierre, pompidor, vignal, cdlh, gracy, jappy From: Michael Pazzani (transmis par jq@lirmm.lirmm.fr (Joel Quinqueton)) Subject: Machine Learning List: Vol. 6 No. 25 Status: RO Date: Sat, 1 Oct 1994 10:40:52 +0600 From: "Douglas H. Fisher" Subject: AI/Stats Workshop Preliminary Call for Participation Fifth International Workshop on ARTIFICIAL INTELLIGENCE and STATISTICS January 4-7, 1995 Ft. Lauderdale, Florida TECHNICAL and TUTORIAL PROGRAM: This is the fifth in a series of workshops that has brought together researchers in Artificial Intelligence and in Statistics to discuss problems of mutual interest. To encourage interaction and a broad exchange of ideas, there will be 20 discussion papers in single session meetings over three days (Jan. 5-7). Two poster sessions will provide the means for presenting and discussing the remaining research papers. Attendance at the workshop is *not* limited to paper presenters. The three days of research presentations will be preceded by a day of tutorials (Jan. 4). The tutorial topics, presenters, and approximate times are: (1) Machine Learning 9:00AM - 12:15PM (Dr. David Aha, Naval Research Lab) (2) Statistical Methods for Inducing 9:00AM - 12:15PM Models from Data (Prof. Steffen Lauritzen, Aalborg U.) (3) Probabilistic Models of Causality 2:00PM - 5:15PM (Prof. Glenn Shafer, Rutgers U.) (4) Statistical Models for Function 2:00PM - 5:15PM Estimation and Classification (Prof. Trevor Hastie, Stanford U.) Notes prepared by the tutorial presenters will be made available at the Workshop. LOCATION: The 1995 Workshop will be held at Pier Sixty Six Resort & Marina 2301 SE 17th Street Causeway Fort Lauderdale, Florida, 33316 USA. Phone: 800-327-3796 (outside Florida) 305-525-6666 Fax : 305-728-3541 The hotel is a 22 acre resort located on the intracoastal waterway. Available amenities include two pools, a 40 person hydrotherapy pool, spa, tennis courts, a children's activity club, seven restaurants and lounges, and water shuttle service to the beach. The Hotel is most conveniently reached from Fort Lauderdale International Airport, which is about 5-10 minutes by car/cab. The Hotel is approximately 45-60 minutes by car from Miami International Airport. The Resort is holding a block of rooms at the rate of $95 US dollars (for single/double) until Dec. 10, 1994. Reservations should be made before this date. The block is held under the name `SOCIETY for ARTIficial Intelligence and Statistics' (or SOCIETY ARTI). REGISTRATION: Registration for the Technical Program (plenary and poster sessions) includes a proceedings of papers submitted by authors, continental breakfasts each day of the technical program, and tentatively, two lunches and one dinner. The Workshop offers student rates and an early-registration discount. Registration rates and instructions can be found on the Registration Form at the end of this Call. Registration for tutorials can also be made in advance using the Registration Form. PROGRAM COMMITTEE: General Chair: D. Fisher Vanderbilt U., USA Program Chair: H. Lenz Free U. Berlin, Germany Members: W. Buntine NASA (Ames), USA J. Catlett AT&T Bell Labs, USA P. Cheeseman NASA (Ames), USA P. Cohen U. of Mass., USA D. Draper U. of Bath, UK Wm. Dumouchel Columbia U., USA A. Gammerman U. of London, UK D. J. Hand Open U., UK P. Hietala U. Tampere, Finland R. Kruse TU Braunschweig, Germany S. Lauritzen Aalborg U., Denmark W. Oldford U. of Waterloo, Canada J. Pearl UCLA, USA D. Pregibon AT&T Bell Labs, USA E. Roedel Humboldt U., Germany G. Shafer Rutgers U., USA P. Smyth JPL, USA Tutorial Chair: P. Shenoy U. Kansas, USA MORE INFORMATION: For more information write dfisher@vuse.vanderbilt.edu or call 615-343-4111. SPONSORS: Society for Artificial Intelligence and Statistics International Association for Statistical Computing *********** Papers accepted for Technical Program Fifth International Workshop on Artificial Intelligence and Statistics PLENARY PAPERS Almond, Schimert (MathSoft) Missing data models as meta-data Brent, Murthy, Lundberg Minimum description length induction (John Hopkins U) for discovering morphemic suffixes Buntine (NASA Ames) Software for data analysis with graphical models: basic tools Chickering, Geiger, Heckerman Learning Bayesian networks: search (MicroSoft) methods and experimental results Cohen, Gregory, Ballesteros, Two algorithms for inducing structural St Amant (U Mass) equation models from data Cooper (U Pitt) Causal discovery from observational data in the presence of selection bias Cox (US West) Using causal knowledge to learn more useful decision rules from data Decatur (Harvard U) Learning in hybrid noise environments using statistical queries Elder (Rice U) Heuristic search for model structure Gebhardt, Kruse Learning possibilistic networks from data (U Braunschweig) Kasahara, Ishikawa, Viewpoint-based measurement of semantic Matsuzawa, Kawaoka similarity between words (Nippon TT) Lubinsky (U Witwatersrand SA) Structured interpretable regression Madigan, Almond (U Washington) Test selection strategies for belief networks Malvestuto (U L'Aquila, IT) Derivation DAGs for inferring interaction models Merz (U Cal Irvine) Dynamic learning bias selection Pearl (UCLA) A causal calculus for statistical research with applications to observational and experimental studies Riddle, Frenedo, Newman Framework for a generic knowledge (Boeing) discovery tool Shafer, Kogan, Spirtes A generalization of the Tetrad (Rutgers) representation theorem St Amant, Cohen (U Mass) Preliminary design for an EDA assistant Yao, Tritchler (U Toronto) Likelihood-based causal inference POSTER PAPERS Aha, Bankert (NRL) A comparative evaluation of sequential feature selection algorithms Ali, Brunk, Pazzani Learning multiple relational rule-based (U Cal Irvine) models Almond (MathSoft) Hypergraph grammars for knowledge-based model construction Anderson, Carlson, Westbrook Tools for analyzing AI programs Hart, Cohen (U Mass) Bergman, Rivest (MIT) Picking the best expert from a sequence Blau (U Rochester) Ploxoma: Test-bed for uncertain inference Breese, Heckerman Probabilistic case-based reasoning (MicroSoft) Burke (U Nevada) Comparing the prediction accuracy of statistical models and artificial neural networks in breast cancer Catlett (ATT) Tailoring rulesets to misclassification cost Chen, Yeh Predicting stock returns with genetic (National Chengchi U) programming Cheng (U Cincinnati) Analysis and Application of the Generalized Mean-Shift Process Cozman, Krotkov (CMU) Truncated Gaussians as tolerance sets Cunningham (U Waikato) Textual data mining De Vel, Li, Coomans Non-Linear dimensionality reduction: (U James Cook, NZ) A comparative performance study DuMouchel, Friedman, Johnson Natural language processing of Hripcsak (Columbia U) radiology reports Esposito, Malerba, Semeraro A further study of pruning methods in (U degli Studi, IT) decision tree induction Feelders, Verkooijen Which method learns most from the data? (U Twente, Netherlands) Franz (CMU) Classifying new words for robust parsing Gelsema (Erasmus U, Abductive reasoning in Bayesian belief The Netherlands) networks using a genetic algorithm Harner, Galfalvy Omega-Stat: An environment for (West Virginia U) implementing intelligent modeling strategies Heckerman, Shachter A decision-based view of causality (MicroSoft) Howe (Colorado St U) Finding dependencies in event streams using local search Jenzarli (U Tampa) Solving influence diagrams using Gibbs sampling John (Stanford U) Robust linear discriminant trees Ketterlin, Gancarski, Korczak Hierarchical clustering of composite (U Louis Pasteur) objects with a variable number of components Kim (Korea Adv. Inst. of Sci. An approach to fitting large influence and Eng.) diagrams Kim, Moon (Syracuse U) Modeling life time data by neural networks Kloesgen (German Nat. Rsch.) Learning from data: Pattern evaluations and search strategies Larranaga, Murga, Poza, Structure learning of Bayesian networks Kuijpers (U Basque, by hybrid genetic algorithms Spain) Lekuona, Lacruz, Lasala Graphical models for dynamic systems (U de Zaragoza, Spain) Liu (U Kansas) Propagation of Gaussian belief functions Martin (U Cal, Irvine) A hypergeometric null hypothesis probability test for feature selection and stopping Martin (U Cal, Irvine) Evaluating and comparing classifiers: Complexity measures Murthy (John Hopkins U) Statistical preprocessing of decision trees Neufeld, Adams, Choy, Philip, Part-of-speech tagging from small Tawfik (U Saskatchewan) data sets Oates, Gregory, Cohen (U Mass) Detecting complex dependencies in categorical data Pazzani (U Cal Irvine) Searching for attribute dependencies in Bayesian classifiers Provan, Singh (Inst. for Learning ``Predictively-Optimal'' Decision Systems Res.) Bayesian Networks Risius, Seidelmann Combining statistics and AI in the (Hahn-Meitner Inst) optimization of semiconductor films for solar cells Shenoy (U Kansas) Representing and solving asymmetric decision problems using valuation networks Srkantan, Srihari Data representations in learning (SUNY Buffalo) Sun, Qiu, Cox (US West) A hill-climbing approach to construct near optimal decision trees Valtorta (U South Carolina) MENTOR: A Bayesian model for prediction and intervention in mental retardation Young, Lubinsky (UNC) Learning from data by guiding the analyst: On the representation, use, and creation of visual statistical strategies *********** Registration Form Fifth International Workshop on Artificial Intelligence and Statistics Participants may register on site. To register in advance of the Workshop send this form and a check (in US dollars) made to the order of **Society for Artificial Intelligence and Statistics** in the appropriate amount to: Doug Fisher Department of Computer Science Box 1679, Station B Vanderbilt University Nashville, Tennessee 37235 USA Advance registration discounts apply if registration is received by Dec. 1, 1994. Name: ________________________________________ Affiliation: _________________________________ Phone: _______________________________________ Fax: _________________________________________ Email: _______________________________________ Address: _____________________________________ _____________________________________ _____________________________________ Technical Program -- check one: ____ Technical Program (regular, by Dec. 1, 1994): $245 ____ Technical Program (student, by Dec. 1, 1994): $155 ____ Technical Program (regular, after Dec. 1, 1994): $295 ____ Technical Program (student, after Dec. 1, 1994): $195 Technical Program Subtotal: $____ Tutorial Program -- check applicable tutorials, if any. Note that the tutorial times may conflict; to avoid conflict at most one selection from (1) and (2), and one selection from (3) and (4) may be made. ____ (1) Machine Learning ____ (regular, by Dec. 1): $ 70 ____ (student, by Dec. 1): $ 45 ____ (regular, after Dec. 1): $ 80 ____ (student, after Dec. 1): $ 55 ____ (2) Statistical Methods for Inducing Models from Data ____ (regular, by Dec. 1): $ 70 ____ (student, by Dec. 1): $ 45 ____ (regular, after Dec. 1): $ 80 ____ (student, after Dec. 1): $ 55 ____ (3) Probabilistic Models of Causality ____ (regular, by Dec. 1): $ 70 ____ (student, by Dec. 1): $ 45 ____ (regular, after Dec. 1): $ 80 ____ (student, after Dec. 1): $ 55 ____ (4) Statistical Models for Function Estimation and Classification ____ (regular, by Dec. 1): $ 70 ____ (student, by Dec. 1): $ 45 ____ (regular, after Dec. 1): $ 80 ____ (student, after Dec. 1): $ 55 Tutorial Program Subtotal: $____ Technical and Tutorial Total: $____