*********************************************************** * CLNL'93 -- Computational Learning and Natural Learning * * Provincetown, Massachusetts * * 10-12 September 1993 * *********************************************************** CLNL'93 is the fourth of an ongoing series of workshops designed to bring together researchers from a diverse set of disciplines --- including computational learning theory, AI/machine learning, connectionist learning, statistics, and control theory --- to explore issues at the intersection of theoretical learning research and natural learning systems. The schedule of presentations appears below, followed by logistics and information on registration ================ ** CLNL'93 Schedule (tentative) ** ======================= Thursday 9/Sept/93: 6:30-9:00 (optional) Ferry (optional): Boston to Provincetown [departs Boston Harbor Hotel, 70 Rowes Wharf on Atlantic Avenue] Friday 10/Sept/93 [CLNL meetings, at Provincetown Inn] 9 - 9:15 Opening remarks 9:15-10:15 Scaling Up Machine Learning: Practical and Theoretical Issues Thomas Dietterich [Oregon State Univ] (invited talk, see abstract below) 10:30-12:30 Paper session 1 What makes derivational analogy work: an experience report using APU Sanjay Bhansali [Stanford]; Mehdi T. Harandi [Univ of Illinois] Scaling Up Strategy Learning: A Study with Analogical Reasoning Manuela M. Veloso [CMU] Learning Hierarchies in Stochastic Domains Leslie Pack Kaebling [Brown] Learning an Unknown Signalling Alphabet Edward C. Posner, Eugene R. Rodemich [CalTech/JPL] 12:30- 2 Lunch (on own) Unscheduled TIME ( Whale watching, beach walking, ... ) ( Poster set-up time; Poster preview (perhaps) ) Dinner (on own) 7 - 10 Poster Session [16 posters] (Hors d'oeuvres) Induction of Verb Translation Rules from Ambiguous Training and a Large Semantic Hierarchy Hussein Almuallim, Yasuhiro Akiba, Takefumi Yamazaki, Shigeo Kaneda [NTT Network Information Systems Lab.] What Cross-Validation Doesn't Say About Real-World Generalization Gunner Blix, Gary Bradshaw, Larry Rendall [Univ of Illinois] Efficient Learning of Regular Expressions from Approximate Examples Alvis Brazma [Univ of Latvia] Capturing the Dynamics of Chaotic Time Series by Neural Networks Gurtavo Deco, Bernd Schurmann [Siemens AG] Learning One-Dimensional Geometrical Patterns Under One-Sided Random Misclassification Noise Paul Goldberg [Sandia National Lab]; Sally Goldman [Washington Univ] Adaptive Learning of Feedforward Control Using RBF Network ... Dimitry M Gorinevsky [Univ of Toronto] A practical approach for evaluating generalization performance Marjorie Klenin [North Carolina State Univ] Scaling to Domains with Many Irrelevant Features Pat Langley, Stephanie Sage [Siemens Corporate Research] Variable-Kernel Similarity Metric Learning David G. Lowe [Univ British Columbia] On-Line Training of Recurrent Neural Networks with Continuous Topology Adaptation Dragan Obradovic [Siemens AG] N-Learners Problem: System of PAC Learners Nageswara Rao, E.M. Oblow [Engineering Systems/Advanced Research] Soft Dynamic Programming Algorithms: Convergence Proofs Satinder P. Singh [Univ of Mass] Integrating Background Knowledge into Incremental Concept Formation Leon Shklar [Bell Communications Research]; Haym Hirsh [Rutgers] Learning Metal Models Astro Teller [Stanford] Generalized Competitive Learning and then Handling of Irrelevant Features Chris Thornton [Univ of Sussex] Learning to Ignore: Psychophysics and Computational Modeling of Fast Learning of Direction in Noisy Motion Stimuli Lucia M. Vaina [Boston Univ], John G. Harris [Univ of Florida] Saturday 11/Sept/93 [CLNL meetings, at Provincetown Inn] 9:00-10:00 Current Tree Research Leo Breiman [UCBerkeley] (invited talk, see abstract below) 10:30-12:30 Paper session 2 Initializing Neural Networks using Decision Trees Arunava Banerjee [Rutgers] Exploring the Decision Forest Patrick M. Murphy, Michael Pazzani [UC Irvine] What Do We Do When There Is Outrageous Data Points in the Data Set? - Algorithm for Robust Neural Net Regression Yong Liu [Brown] A Comparison of RBF and MLP Networks for Classification of Biomagnetic Fields Martin F. Schlang, Ralph Neunier, Klaus Abraham-Fuchs [Siemens AG] 12:30- 2 Lunch (on own) 2:30- 3:30 TBA (invited talk) Yann le Cun [ATT] 4:00- 6:00 Paper session 3 On Learning the Neural Network Architecture: An Average Case Analysis Mostefa Golea [Univ of Ottawa] Fast (Distribution Specific) Learning Dale Schuurmans [Univ of Toronto] Computational capacity of single neuron models Anthony Zador [Yale Univ School of Medicine] Probalistic Self-Structuring and Learning A.D.M. Garvin, P.J.W. Rayner [Cambridge] 7:00- 9 Banquet dinner Sunday 12/Sept/93 [CLNL meetings, at Provincetown Inn] 9 -11 Paper session 4 Supervised Learning from real and Discrete Incomplete Data Zoubin Ghaharamani, Michael Jordan [MIT] Model Building with Uncertainty in the Independent Variable Volker Tresp, Subutai Ahmad, Ralph Neuneier [Siemens AG] Supervised Learning using Unclassified and Classified Examples Geoff Towell [Siemens Corp. Res.] Learning to Classify Incomplete Examples Dale Schuurmans [Univ of Toronto]; R. Greiner [Siemens Corp. Res.] 11:30 -12:30 TBA (invited talk) Ron Rivest [MIT] 12:30 - 2 Lunch (on own) 3:30 - 6:30 Ferry (optional): Provincetown to Boston Depart from Boston (on own) ------ ------ Scaling Up Machine Learning: Practical and Theoretical Issues Thomas G. Dietterich Oregon State University and Arris Pharmaceutical Corporation Supervised learning methods are being applied to an ever-expanding range of problems. This talk will review issues arising in these applications that require further research. The issues can be organized according to the problem-solving task, the form of the inputs and outputs, and any constraints or prior knowledge that must be considered. For example, the learning task often involves extrapolating beyond the training data in ways that are not addressed in current theory or engineering experience. As another example, each training example may be represented by a disjunction of feature vectors, rather than a unique feature vector as is usually assumed. More generally, each training example may correspond to a manifold of feature vectors. As a third example, background knowledge may take the form of constraints that must be satisfied by any hypothesis output by a learning algorithm. The issues will be illustrated using examples from several applications including recent work in computational drug design and ecosystem modelling. -------- Current Tree Research Leo Breiman Deptartment of Statistics University of California, Berkeley This talk will summarize current research by myself and collaborators into methods of enhancing tree methodology. The topics covered will be: 1) Tree optimization 2) Forming features 3) Regularizing trees 4) Multiple response trees 5) Hyperplane trees These research areas are in a simmer. They have been programmed and are undergoing testing. The results are diverse. -------- -------- Programme Committee: Andrew Barron, Russell Greiner, Tom Hancock, Steve Hanson, Robert Holte, Michael Jordan, Stephen Judd, Pat Langley, Thomas Petsche, Tomaso Poggio, Ron Rivest, Eduardo Sontag, Steve Whitehead Workshop Sponsors: Siemens Corporate Research and MIT Laboratory of Computer Science ================ ** CLNL'93 Logistics ** ======================= Dates: The workshop begins at 9am Friday 10/Sept, and concludes by 3pm Sunday 12/Sept, in time to catch the 3:30pm Provincetown--Boston ferry. Location: All sessions will take place in the Provincetown Inn (800 942-5388); we encourage registrants to stay there. Provincetown Massachusetts is located at the very tip of Cape Cod, jutting into the Atlantic Ocean. Transportation: We have rented a ship from The Portuguese Princess to transport CLNL'93 registrants from Boston to Provincetown on Thursday 9/Sept/93, at no charge to the registrants. We will also supply light munchies en route. This ship will depart from the back of Boston Harbor Hotel, 70 Rowes Wharf on Atlantic Avenue (parking garage is 617 439-0328); tentatively at 6:30pm. If you are interested in using this service, please let us know ASAP (via e-mail to clnl93@learning.scr.siemens.com) and also tell us whether you be able to make the scheduled 6:30pm departure. (N.b., this service replaces the earlier proposal, which involved the Bay State Cruise Lines.) The drive from Boston to Provincetown requires approximately two hours. There are cabs, busses, ferries and commuter airplanes (CapeAir, 800 352-0714) that service this Boston--Provincetown route. The Hyannis/Plymouth bus (508 746-0378) leaves Logan Airport at 8:45am, 11:45am, 2:45pm, 4:45pm on weekdays, and arrives in Provincetown about 4 hours later; its cost is $24.25. For the return trip (only), Bay State Cruise Lines (617 723-7800) runs a ferry that departs Provincetown at 3:30pm on Sundays, arriving at Commonwealth Pier in Boston Harbor at 6:30pm; its cost is $15/person, one way. Inquiries: For additional information about CLNL'93, contact clnl93@learning.scr.siemens.com or CLNL'93 Workshop Learning Systems Department Siemens Corporate Research 755 College Road East Princeton, NJ 08540--6632 To learn more about Provincetown, contact their Chamber of Commerce at 508 487-3424. ================ ** CLNL'93 Registration ** ======================= Name: ________________________________________________ Affiliation: ________________________________________________ Address: ________________________________________________ ________________________________________________ Telephone: ____________________ E-mail: ____________________ Select the appropriate options and fees: Workshop registration fee ($50 regular; $25 student) ___________ Includes * attendance at all presentation and poster sessions * the banquet dinner on Saturday night; and * a copy of the accepted abstracts. Hotel room ($74 = 1 night deposit) ___________ [This is at the Provincetown Inn, assuming a minimum stay of 2 nights. The total cost for three nights is $222 = $74 x 3, plus optional breakfasts. Room reservations are accepted subject to availability. See hotel for cancellation policy.] Arrival date ___________ Departure date _____________ Name of person sharing room (optional) __________________ [Notice the $74/night does correspond to $37/person per night double-occupancy, if two people share one room.] # of breakfasts desired ($7.50/bkfst; no deposit req'd) ___ Total amount enclosed: ___________ If you are not using a credit card, make your check payable in U.S. dollars to "Provincetown Inn/CLNL'93", and mail your completed registration form to Provincetown Inn/CLNL P.O. Box 619 Provincetown, MA 02657. If you are using Visa or MasterCard, please fill out the following, which you may mail to above address, or FAX to 508 487-2911. Signature: ______________________________________________ Visa/MasterCard #: ______________________________________________ Expiration: ______________________________________________ -- | Russ Greiner Siemens Corporate Research | | greiner@learning.scr.siemens.com (609) 734-3627 |