CP for AI and Stats Workshop
Wray Buntine
wray at ptolemy.arc.nasa.gov
Wed Nov 4 17:34:55 EST 1992
NOTE: This second call for participation contains a list of papers
and posters being presented.
;;;-------------------------- Cut here -----------------------------------
2nd Call for Participants
and
Schedule for
Fourth International Workshop on
Artificial Intelligence
and
Statistics
January 3-6, 1993
Ft. Lauderdale, Florida
PURPOSE:
This is the fourth in a series of workshops which has
brought together researchers in Artificial Intelligence and in
Statistics to discuss problems of mutual interest. The result has
been an unqualified success. The exchange has broadened research
in both fields and has strongly encouraged interdisciplinary work.
This workshop will have as its primary theme:
``Selecting models from data''
FORMAT:
Approximately 60 papers by leading researchers in Artificial
Intelligence and Statistics have been selected for presentation.
To encourage interaction and a broad exchange of ideas, the
presentations will be limited to 20 discussion papers in single
session meetings over the three days. Focussed poster sessions,
each with a short presentation, provide the means for presenting
and discussing the remaining 40 research papers.
Attendance at the workshop is *not* limited.
The three days of research presentations will be preceded by a day
of tutorials. These are intended to expose researchers in each
field to the methodology used in the other field.
LANGUAGE:
The language will be English.
FORMAT:
One day of tutorials and three days of focussed poster sessions,
presentations and panels. The presentations are scheduled in the
mornings and evenings, leaving
the afternoons free for discussions in more relaxed environments.
SCHEDULE:
Sun: Jan. 3rd.
--------------
Sunday is scheduled for tutorials. There are 4 -- at most
two can be attended without conflict.
AI for statisticians
Morning: Doug Fisher -- Intro. to learning
including neural networks
Afternoon: Judea Pearl -- Graphical models,
causal reasoning,
and qualitative decision making.
Statistics for AI
Morning: Wray Buntine -- Introduction to Statistics and
Decision Analysis
Afternoon: Daryl Pregibon -- Overview of Statistical Models
Mon: Jan. 4th.
---------------
8:30--10:00
1st. Session---Model Selection
Peter Cheeseman--Introduction: "Overview of Model Selection"
Beat E. Neuenschwander, Bernard D. Flury, "Principal Components and
Model Selection".
Cullen Schaffer, "Selecting a Classification Method by
Cross-Validation".
Stanley Sclove, "Small-Sample and Large-Sample Statistical Model
Selection Criteria".
--------------------------------------------------------
10:00--10:30 break
--------------------------------------------------------
10:30--12:00
2nd. Session---Model Comparison
C. Feng, A. Sutherland, R. King, S. Muggleton, R. Henery, Comparison
of Classification Algorithms in Machine Learning, Statistics, and
Neural Networks (DRAFT).
Richard D. De Veaux, "A Tale of Two Nonparametric Estimation Schemes:
MARS and Neural Networks".
Christopher de Vaney, "A Support Architecture for Statistical
Meta-Information with Knowledge-Based Extensions".
+ Discussion (speakers and audience)
---------------------------------------------------------
Lunch (provided)
---------------------------------------------------------
1:30--3:00 1st panel--Alternative Approaches to Model Selection
Panel Moderator: Wayne Oldford
---------------------------------------------------------
3:00--3:30 break
---------------------------------------------------------
3:30--5:00
3rd. Session---Statistics in AI
Nathaniel G. Martin, James F. Allen, "Statistical Probabilities for
Planning".
Arcot Rajasekar, "On Closures in Knowledge Base Systems".
Steffen L. Lauritzen, B. Thiesson, DJ Spiegelhalter, "Diagnostic
Systems Created by Model Selection Methods-A Case Study".
Vladimir Cherkassky, "Statistical and Neural Network Techniques For
Nonparametric Regression".
--------------------------------------------------------
--------------------------------------------------------
Tue: Jan. 5th.
--------------
8:30--10:00
4th Session---Causal Models
Floriana Esposito, Donato Malerba, Giovanni Semeraro, "Comparison of
Statistical Methods for Inferring Causation".
J. Pearl and N. Wermuth, "When Do Association Graphs have Causal
Explanations".
Richard Scheines, "Inferring Causal Structure Among Unmeasured
Variables".
+ Invited speaker
--------------------------------------------------------
10:00--10:30 break
--------------------------------------------------------
10:30--12:00
5th Session---Very Short "poster" presentations
--------------------------------------------------------
break--rest of afternoon off
--------------------------------------------------------
6:00 -7:30 buffet supper (provided)
7:30 -8:40 1st poster session (see list of posters at end)
8:50 -10:00 2nd poster session (preceded by 10 minute changeover)
--------------------------------------------------------
--------------------------------------------------------
Wed: Jan. 6th.
--------------
8:30--10:00
6th Session---Influence Diagrams and Probabilistic Networks
Remco R Bourckaert, "Conditional Dependence in Probabilistic
Networks".
Geoffrey Rutledge MD, Ross Shachter, "A Method for the Dynamic
Selection of Models Under Time Constraints".
Gregory M. Provan, "Diagnosis Over Time Using Temporal Influence
Diagrams".
+ Discussion (speakers and audience)
--------------------------------------------------------
10:00--10:30 break
--------------------------------------------------------
10:30--12:00
7th Session---AI in Statistics
R. W. Oldford, D. G. Anglin, "Modelling Response Models in Software".
D. J. Hand, "Statistical Strategy: Step 1".
David Draper, "Assessment and Propagation of Model Uncertainty".
Debby Keen, Arcot Rajasekar, "Reasoning With Inductive Dependencies"
---------------------------------------------------------
Lunch (provided)
---------------------------------------------------------
1:30--3:00 2nd panel
3:00--Business meeting
-----------------------Posters--------------------------------
Russell G. Almond, "An Ontology for Graphical Models".
D.L. Banks, R.A. Maxion, "Comparative Evaluation of New Wave Methods
for Model Selection".
Raj Bhatnagar, Laveen N Kanal, "Models from Data for Various Types of
Reasoning".
Djamel Bouchaffra, Jacques Rouault, "Different ways of capturing the
observations in a nonstationary hidden Markov model: application to
the problem of Morphological Ambiguities".
Victor L. Brailovsky, "Model selection by perturbing data set
(extended abstract)".
Carla E. Brodley, Paul Utgoff, "Dynamic Recursive Model Class
Selection for Classifier Construction Extended Abstract".
W. Buntine, "On Generic Priors in Learning".
Paul R. Cohen, "Path Analysis Models of an Autonomous Agent in a
Complex Environment".
Sally Jo Cunningham, Paul Denize, "A Tool for Model Genertion and
Knowledge Acquisition".
Luc Devroye, Oliver Kamoun, "Probabilistic Min-Max Trees".
E. Diday, P. Brito and E. Mfoumoune, "Modelling Probabilistic Data by
Conceptual Pyramidal Clustering".
Kris Dockx, James Lutsko, "SA/GA: Survival of the Fittest in Alaska".
Zbigniew Duszak, Jerzy Grzymala-Busse, Waldemar W. Koczkoda, "Rule
Induction Based on Statistics and Rough Set Theory".
J. J. Faraway, "Choise of Order in Regression Strategy".
Karina Gibert, "Combining a Knowledge-based System and a Clustering
Method For an Inductive Construction of Models".
Scott D. Goodwin, Eric Neufeld, Andre Trudel, "Extrapolating Definite
Integral Information".
Jonathan Gratch, Gerald DeJong, "Rational Learning: Finding a Balance
Between Utility and Efficiency".
A. K. Gupta, "Information Theoretic Approach to Some Multivariate
Tests of Homogeneity".
Paula Hietala, "Statistical Reasoning to Enhance User Modelling in
Consulting Systems".
Adele Howe, Paul R. Cohen, "Detecting and Explaining Dependencies in
Execution Traces".
Sung-Ho Kim, "On Combining Conditional Influence Diagrams".
Willi Klosgen, "Discovery in Databases".
G. J. Knafl, A. Semrl, "Software Reliability Expert (SRX)".
Bing Leng, Bruce Buchanan, "Using Knowledge-Assisted Discriminant
Analysis to Generate New Comparative Terms for Symblic Learner".
James F. Lutsko, Bart Kuijpers, "Simulated Annealing in the
Construction of Near-Optimal Decision Trees".
Yong Ma, David Wilkins, John S. Chandler, "An Extended Bayesian Belief
Function Approach to Handle Noise in Inductive Learning".
Izhar Matzkevich, Bruce Abramson, "Towards Prior Compromise in Belief
Networks (Extended Abstract)".
Johnathan Oliver, "Decision Graphs - An Extension of Decision Trees".
Egmar Rodel, "A Knowledge Based System for Testing Bivariate
Dependence".
A.R. Runnaalls, "Global vs Local Sampling Procedures for Inference on
Directed Graphs".
David Russell, "Statistical Inferencing in a Real-Time Heuristic
Controller".
Geoffrey Rutledge MD, Ross Shachter, "A Method for the
Dynamic Selection of Models Under Time Constraints".
Steven Salzberg, David Aha, "Learning to Catch: Applying Nearest
Neighbor algorithms to Dynamic Control Tasks".
D. Moreira dos Santos, "Selecting a Frailty Model for Longitudinal
Breast Cancer Data".
Glenn Shafer, "Recursion in Join Trees".
P. Shenoy, "Searching For Alternative Representation of Data: A Case
for Tetrad".
Hidetoshi Shimodaira, "A New Criterion for Selecting Models from
Partially Observed Data".
P. Smyth, "The Nature of Class Labels in Supervised Learning".
Peter Spirtes, Clark Glymour, "Inference, Intervention and
Prediction".
Marco Valtora, R. Mechling, "PaCCIN: A parallel Constructor of Markov
Networks".
Aaron Wallack, Ed Nicolson, "Optimal Design of Reflective Sensors
Using Probabilistic Analysis".
Bradley Whitehall, David Sirag, "Clustering of Smybolically Described
Events for Prediction of Numeric Attributes".
Nevin Lianwen Zhang, Runping Qi, David Poole, "Minizing Decision Table
Sizes in Stepwise-Decomposable Influence Diagrams".
Ping Zhang, "On the Choise of Penalty term in Generalized FPE
criterion".
PROGRAM COMMITTEE:
General Chair: R.W. Oldford U. of Waterloo, Canada
Programme Chair: P. Cheeseman NASA (Ames), USA
Members:
W. Buntine NASA (Ames), USA
Wm. Dumouchel BBN, USA
D.J. Hand Open University, UK
W.A. Gale AT&T Bell Labs, USA
H. Lenz Free University, Germany
D. Lubinsky AT&T Bell Labs, USA
M. Deutsch-McLeish U. of Guelph, Canada
E. Neufeld U. of Saskatchewan, Canada
J. Pearl UCLA, USA
D. Pregibon AT&T Bell Labs, USA
P. Shenoy U. of Kansas, USA
P. Smythe JPL, USA
SPONSORS:
Society for Artificial Intelligence And Statistics
International Association for Statistical Computing
REGISTRATION: All fees paid:
Before Dec 1, 1992 After Dec 1, 1992
Scientific programme: $225 $275
Full-time Students $135 $175
- Registration fee includes three continental breakfasts and two
lunches supplied at the workshop site.
- Students must supply proof of full-time student status (at the
workshop) to be eligible for reduced rates.
A REGISTRATION FORM APPEARS AT THE END OF THIS MESSAGE.
TUTORIALS: There are four three hour tutorials planned.
Two introducing statistical methodology to AI researchers
and two introducing AI methodology to statistical researchers.
Before Dec 1, 1992 After Dec 1, 1992
Per Tutorial $65 $75
Full-time Students $40 $45
The tutorials are introductions to the following topics:
1. Learning, including a discussion of neural networks.
Speaker: Doug Fisher, Vanderbilt University
Orientation: AI for statisticians
2. Graphical models, causal reasoning, and qualitative
decision making.
Speaker: Judea Pearl, UCLA
Orientation: AI for statisticians.
3. Overview of statistical models.
Emphasis on generalised linear and additive models.
Speaker: Daryl Pregibon, AT&T Bell Labs
Orientation: Statistics for AI researchers.
4. Introduction to Statistics.
General introduction to statistical topics
Speaker: Wray Buntine, NASA Ames
Orientation: Statistics for AI researchers.
Please indicate which tutorial(s) you are registering for.
PAYMENT OF FEES:
All workshop fees are payable by cheque or money order in U.S.
dollars (drawn on a U.S. bank) to the Society for Artificial
Intelligence and Statistics.
Send cheque or money order to:
R.W. Oldford
Chair, 4th Int'l Workshop on A.I. & Stats.
Dept. of Statistics & Actuarial Science
University of Waterloo
Waterloo, Ontario
N2L 3G1
CANADA
NOTE: ACCOMODATIONS MUST BE ARRANGED DIRECTLY WITH THE HOTEL.
ACCOMODATION: We have arranged for a block of rooms to be available to
participants at the Workshop site hotel for $85 per night
(single or double + tax). Arrangements must be made
directly with the hotel. Please mention the Workshop on
all communications. Rates are available Jan 1 to Jan 10
(if booked before Dec 17, 1992).
Pier 66 Resort and Marina
2301 S.E. 17th Street Causeway
Ft. Lauderdale, Florida 33316
(305) 525 6666
(800) 327 3796 (USA only)
(800) 432 1956 (Florida only)
Fax: (305) 728 3551
Telex: 441-650
REGISTRATION FORM:
4th International Workshop on
AI and Statistics
January 3-6, 1993
Ft. Lauderdale, Florida
Name: _______________________________
Affiliation: _______________________________
Address: _____________________________________________
_____________________________________________
_____________________________________________
_____________________________________________
e-mail: _____________________________________________
Fax: ___________________________
Phone: ___________________________
Scientific Programme Registration ...................... US$___________
Tutorial 1. Learning ................................... US$___________
Tutorial 2. Causal Reasoning ........................... US$___________
Tutorial 3. Statistical Models ......................... US$___________
Tutorial 4. Introduction to Statistics ................. US$___________
_______________________________________________________________________
Total Payment .......................................... US$___________
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