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Machine Learning List Vol. 5 No. 23
Machine Learning List: Vol. 5 No. 23
Monday, November 1, 1993
Contents:
Machine Learning List: Vol. 5 No. 23
FOIL 6.0
Machine Learning Postdoc Position at CMU
AI/Stats list
Tech reports available
Clustering query
Santa Fe Time Series Competition book out
ICLP'94 - Call For Papers
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<X>/<N> or N.Z where X and N are
the volume and number of the issue; ID: anonymous PASSWORD: <your mail address>
----------------------------------------------------------------------
Date: Fri, 29 Oct 1993 11:07:26 +1000
From: Ross Quinlan <quinlan@ml2.cs.su.oz.au>
Subject: FOIL 6.0
FOIL6.0 is a fairly comprehensive (and overdue) rewrite of FOIL5.2.
The code is now more compact, better documented, and faster for most
tasks. The language has changed to ANSI C.
In the process of rewriting, several small changes have been made to
the algorithm. Some of these correct minor glitches (such as
restoring the number of weak literals after search is restarted).
Others significantly change the behaviour of FOIL: for instance, the
checks before literal evaluation have been strengthened and further
pruning heuristics introduced.
FOIL6.0 is available by anonymous ftp from ftp.cs.su.oz.au (129.78.8.208).
Login as anonymous with your email address as password. The file is
"~ftp/pub/foil6.sh" (a shar file).
Comments and bug reports are most welcome!
Ross Quinlan
Mike Cameron-Jones
------------------------------
Date: Tue, 19 Oct 93 18:47:57 EDT
From: Tom.Mitchell@cs.cmu.EDU
Subject: Machine Learning Postdoc Position at CMU
I have an opening for a postdoctoral researcher or visiting scientist
in Machine Learning at Carnegie Mellon. The position will involve
basic research on machine learning algorithms, as well as their
application to personal software assistants that learn from their
users. More specifically, we have recently developed a personal
calendar assistant that learns scheduling preferences of its users by
generalizing from meetings that have been scheduled in the past. The
postdoc will be expected to work closely with me to lead this research
project in some new directions. For example, we might extend this
system by improving its learning abilities, developing methods for
cooperative learning among groups of personal assistants, and
considering new applications such as a learning newsgroup reader. If
interested, please send a short vitae and names of three references to
Tom.Mitchell@cs.cmu.edu. I expect the opening to be filled sometime
between December and next summer.
------------------------------
From: "Douglas H. Fisher" <dfisher@vuse.vanderbilt.edu>
Subject: AI/Stats list
A new mailing list for those interested in AI and Statistics
has been created. Requests to be added to this mailing list
should be directed to
ai-stats-request@watstat.uwaterloo.ca
Organization of the 1995 International AI and Statistics Workshop
has begun. Look for announcements in this and other newsgroups.
Doug Fisher, General Chair
------------------------------
From: honavar@iastate.edu
Subject: tech reports available
Date: Tue, 26 Oct 93 14:17:12 CDT
The following tech reports (in postscript format)
can be obtained by sending email to almanac@cs.iastate.edu
The body of the email message should contain:
send tr <TR#>
where <TR#> is the number of the tech report e.g., TR93-25
TR93-22
Toward Learning Systems That Integrate
Different Strategies and Representations
Vasant Honavar
TR93-25
Efficient Learning of Regular Languages Using Teacher-Supplied
Positive Samples and Learner-Generated Queries
Rajesh Parekh & Vasant Honavar
------------------------------
Date: Sun, 24 Oct 93 17:19:11 CDT
From: "Douglas H. Fisher" <dfisher@vuse.vanderbilt.edu>
To: ml@ics.uci.edu, pazzani@ics.uci.edu
Subject: clustering query
The forms of iterative optimization in clustering that I
am familiar with begin with some initial clustering,
and then iteratively move single objects around
in search of a better clustering according to some
objective measure.
I have built a system that forms an initial hierarchical
clustering, and then moves top-down through the hierarchy,
at each level `reclassifying' entire clusters (subtrees)
in search of a better partition. This top-down pass
terminates at leaves, where single objects are reclassified
in the global hierarchical structure. In general, several
top-down passes may be necessary before the hierarchical
clustering `stabilizes'.
If you know of published work along similar lines, either
similar systems, or work related to the more general issue
of reclassifying object sets (versus single objects),
then please send me citations at dfisher@vuse.vanderbilt.edu
Thank you, Doug Fisher
------------------------------
Subject: Santa Fe Time Series Competition book out
Date: Fri, 22 Oct 93 01:40:46 MDT
From: weigend@sabai.cs.colorado.edu
Announcing book on the results of the Santa Fe Time Series Competition:
____________________________________________________________________
Title: TIME SERIES PREDICTION:
Forecasting the Future and Understanding the Past.
Editors: Andreas S. Weigend and Neil A. Gershenfeld
Publisher: Addison-Wesley, September 1993.
Paperback ISBN 0-201-62602-0 US$32.25 (672 pages)
Hardcover ISBN 0-201-62601-2 US$49.50 (672 pages)
The rest of this posting gives some background,
ordering information, and the table of contents.
____________________________________________________________________
Most observational disciplines, such as physics, biology, and finance,
try to infer properties of an unfamiliar system from the analysis of a measured
time record of its behavior. There are many mature techniques associated with
traditional time series analysis. However, during the last decade, several new
and innovative approaches have emerged (such as neural networks and time-delay
embedding), promising insights not available with these standard methods.
Unfortunately, the realization of this promise has been difficult.
Adequate benchmarks have been lacking, and much of the literature has been
fragmentary and anecdotal.
This volume addresses these shortcomings by presenting the results of a
careful comparison of different methods for time series prediction and
characterization. This breadth and depth was achieved through the Santa Fe
Time Series Prediction and Analysis Competition, which brought together an
international group of time series experts from a wide variety of fields to
analyze data from the following common data sets:
- A physics laboratory experiment (NH3 laser)
- Physiological data from a patient with sleep apnea
- Tick-by-tick currency exchange rate data
- A computer-generated series designed specifically for the Competition
- Astrophysical data from a variable white dwarf star
- J. S. Bach's last (unfinished) fugue from "Die Kunst der Fuge."
In bringing together the results of this unique competition, this volume serves
as a much-needed survey of the latest techniques in time series analysis.
Andreas Weigend received his Ph.D. from Stanford University
and was a postdoc at Xerox PARC. He is Assistant Professor in
the Computer Science Department and at the Institute of
Cognitive Science at the University of Colorado at Boulder.
Neil Gershenfeld received his Ph.D. from Cornell University
and was a Junior Fellow at Harvard University. He is Assistant
Professor at the Media Lab at MIT.
____________________________________________________________________
Order it through your bookstore, or directly from the publisher by
- calling the Addison-Wesley Order Department at 1-800-358-4566,
- faxing 1-800-333-3328,
- emailing <marcuss@world.std.com>, or
- writing to Advanced Book Marketing
Addison-Wesley Publishing
One Jacob Way
Reading, MA 01867, USA.
VISA, Mastercard, and American Express and checks are accepted.
When you prepay by check, Addison-Wesley pays shipping and handling
charges. If payment does not accompany your order, shipping charges
will be added to your invoice. Addison-Wesley is required to remit
sales tax to the following states: AZ, AR, CA, CO, CT, FL, GA, IL, IN,
LA, ME, MA, MI, MN, NY, NC, OH, PA, RI, SD, TN, TX, UT, VT, WA, WV,
WI.
_____________________________________________________________________
TABLE OF CONTENTS
xv Preface
Andreas S. Weigend and Neil A. Gershenfeld
1 The Future of Time Series: Learning and Understanding
Neil A. Gershenfeld and Andreas S. Weigend
Section I. DESCRIPTION OF THE DATA SETS__________________________________
73 Lorenz-Like Chaos in NH3-FIR Lasers
Udo Huebner, Carl-Otto Weiss, Neal Broadus Abraham, and Dingyuan Tang
105 Multi-Channel Physiological Data: Description and Analysis
David R. Rigney, Ary L. Goldberger, Wendell C. Ocasio, Yuhei Ichimaru, George B. Moody, and Roger G. Mark
131 Foreign Currency Dealing: A Brief Introduction
Jean Y. Lequarre
139 Whole Earth Telescope Observations of the White Dwarf Star (PG1159-035)
J. Christopher Clemens
151 Baroque Forecasting: On Completing J.S. Bach's Last Fugue
Matthew Dirst and Andreas S. Weigend
Section II. TIME SERIES PREDICTION________________________________________
175 Time Series Prediction by Using Delay Coordinate Embedding
Tim Sauer
195 Time Series Prediction by Using a Connectionist Network with Internal Delay Lines
Eric A. Wan
219 Simple Architectures on Fast Machines: Practical Issues in Nonlinear Time Series Prediction
Xiru Zhang and Jim Hutchinson
243 Neural Net Architectures for Temporal Sequence Processing
Michael C. Mozer
265 Forecasting Probability Densities by Using Hidden Markov Models with Mixed States
Andrew M. Fraser and Alexis Dimitriadis
283 Time Series Prediction by Using the Method of Analogues
Eric J. Kostelich and Daniel P. Lathrop
297 Modeling Time Series by Using Multivariate Adaptive Regression Splines (MARS)
P.A.W. Lewis, B.K. Ray, and J.G. Stevens
319 Visual Fitting and Extrapolation
George G. Lendaris and Andrew M. Fraser
323 Does a Meeting in Santa Fe Imply Chaos?
Leonard A. Smith
Section III. TIME SERIES ANALYSIS AND CHARACTERIZATION___________________
347 Exploring the Continuum Between Deterministic and Stochastic Modeling
Martin C. Casdagli and Andreas S. Weigend
367 Estimating Generalized Dimensions and Choosing Time Delays: A Fast Algorithm
Fernando J. Pineda and John C. Sommerer
387 Identifying and Quantifying Chaos by Using Information-Theoretic Functionals
Milan Palus
415 A Geometrical Statistic for Detecting Deterministic Dynamics
Daniel T. Kaplan
429 Detecting Nonlinearity in Data with Long Coherence Times
James Theiler, Paul S. Linsay, and David M. Rubin
457 Nonlinear Diagnostics and Simple Trading Rules for High-Frequency Foreign Exchange Rates
Blake LeBaron
475 Noise Reduction by Local Reconstruction of the Dynamics
Holger Kantz
Section IV. PRACTICE AND PROMISE_________________________________________
493 Large-Scale Linear Methods for Interpolation, Realization, and
Reconstruction of Noisy, Irregularly Sampled Data
William H. Press and George B. Rybicki
513 Complex Dynamics in Physiology and Medicine
Leon Glass and Daniel T. Kaplan
529 Forecasting in Economics
Clive W.J. Granger
539 Finite-Dimensional Spatial Disorder: Description and Analysis
V.S. Afraimovich, M.I. Rabinovich, and A.L. Zheleznyak
557 Spatio-Temporal Patterns: Observations and Analysis
Harry L. Swinney
569 Appendix: Accessing the Server
571 Bibliography (800 references)
631 Index
------------------------------
Date: Thu, 21 Oct 93 09:36:18 +0100
From: Fosca Giannotti <fosca@orione.cnuce.cnr.it>
Subject: ICLP'94 - Call For Papers
Call For Papers
INTERNATIONAL CONFERENCE ON LOGIC PROGRAMMING (ICLP'94)
S. Margherita Ligure, Italy, 13-18 June 1994
Sponsored by the Association of Logic Programming
Logic programming originates from the discovery that a subset of
predicate logic could be given a procedural interpretation which was
first embodied in the programming language Prolog. The unique features
of logic programming make it appealing for numerous applications in
artificial intelligence, computer-aided design and verification,
databases, and operations research as well as to explore parallel and
concurrent computing. The last two decades have witnessed substantial
developments in this field from its foundation to implementation,
applications, and the exploration of new language designs.
ICLP'94 is the eleventh international conference on logic programming
and is one of the two major annual international conferences reporting
recent research results in logic programming. The technical program
for the conference will include tutorials, invited lectures, and
presentations of refereed papers and posters. Papers are welcome on
all aspects of logic programming, including, but not limited to:
Applications Language design
Architecture Natural language
Artificial Intelligence Parallelism
Concurrency Programming methodology
Constraints Proof theory
Databases Semantics and foundations
Environments Static analysis
Higher-order programming Theorem Proving
Implementation Types
Papers must be written in English, must not exceed 15 pages (including
references and figures), and must contain a cover page including the
following: a 200 word abstract, keywords, and postal and electronic
mailing addresses as well as phone numbers and fax numbers of the
responsible author. Submitted papers should not have been previously
published or being submitted to any journals or refereed conferences.
Accepted papers must be presented at the conference.
Send SIX (6) copies of your submission by NOVEMBER 15, 1993 to
Pascal Van Hentenryck
Brown University, Box 1910
Providence, RI 02912 (USA)
Email: pvh@cs.brown.edu
Phone: +1 401 863 76 34
Fax: +1 401 863 76 57
Authors will be notified of the acceptance or rejection of their
papers by FEBRUARY 21, 1994. Final versions of the accepted
papers must be received in camera-ready form by MARCH 15, 1994.
The proceedings will be published by MIT Press.
ICLP'94 will take place in Santa Margherita Ligure, a small town in
the Italian Riviera close to Genova, the largest city of Liguria.
Close to the conference site is the worldwide famous village of
Portofino, pearl of the Mediterranean Sea and marine natural park; not
far from Santa Margherita is also the pleasant resort area of "Cinque
Terre", consisting of five pictoresque villages on the rocky coast
which can be reached by train or boat only.
PROGRAM COMMITTEE
Khayri Ali Sweden
Maurice Bruynooghe Belgium
Philippe Codognet France
Yves Deville Belgium
Herve Gallaire France
Chris Hogger UK
Joxan Jaffar USA
Giorgio Levi Italy
Jan Maluszynski Sweden
Kim Marriott Australia
Maurizio Martelli Italy
Lee Naish Australia
Frank Pfenning USA
David Poole Canada
Antonio Porto Portugal
Raghu Ramakrishnan USA
M. Rodriguez-Artalejo Spain
Gert Smolka Germany
V.S. Subrahmanian USA
Peter Szeredi Hungary
Evan Tick USA
Kazunori Ueda Japan
Pascal Van Hentenryck USA
Peter Van Roy France
Andrei Voronkov Sweden
Mark Wallace Germany
Rong Yang UK
GENERAL CHAIR
Maurizio Martelli (Genova)
PROGRAM CHAIR
Pascal Van Hentenryck (Brown)
POSTER CHAIR
Lee Naish (Melbourne)
WORKSHOP CHAIR
Catuscia Palamidessi (Genova)
PUBLICITY CHAIR
Fosca Giannotti (Pisa)
ORGANIZING COMMITTEE
Rosa Maria Bottino (IMA-CNR)
Giorgio Delzanno (DISI)
Giuseppe Marino (DIST)
Alessandro Messora (DISI)
LOCAL ORGANIZATION
Piera Ponta (CGR)
------------------------------
End of ML-LIST (Digest format)
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