ETAI-DRU-Newsletter-02

Salem BENFERHAT (benferha@irit.fr)
Sun, 9 Aug 1998 22:27:04 +0200 (MET DST)

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NEWSLETTER ON DECISION AND REASONING UNDER UNCERTAINTY
Issue 98002 Editors: Salem Benferhat, Henri Prade 22.7.1998
Back issues available at http://www.ida.liu.se/ext/etai/dru/binf.html

For complete information concerning ETAI-DRU area, and for the call for papers
see: http://www.ida.liu.se/ext/etai
**************************************************************************

This first newsletter after the introductory one contains:
1. Abstract of a submitted paper by David Poole
2. Technical program of UAI-98
3. Call for papers of Ecsqaru-99
4. Call for papers of Uncertainty-99
5. Table of contents of IPMU-98 proceedings

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Important: For those which have not yet subscribed, please send the
following information by email (to benferhat@irit.fr, prade@irit.fr):

Last and first name, affiliation, email address, personal web-page

in order to continue receiving Newsletters and News Journals.
**************************************************************************

==========================================================================
1. Abstract of a submited paper by David Poole
==========================================================================

Title: Decision Theory, the Situation Calculus and Conditional Plans.
Authors: David Poole

Abstract:
This paper shows how to combine decision theory and logical
representations of actions in a manner that seems natural for both. In
particular, we assume an axiomatization of the domain in terms of
situation calculus, using what is essentially Reiter's solution to the
frame problem, in terms of the completion of the axioms defining the state
change. Uncertainty is handled in terms of the independent choice logic,
which allows for independent choices and a logic program that gives the
consequences of the choices. As part of the consequences are a
specification of the utility of (final) states, and how (possibly noisy)
sensors depend on the state. The robot adopts conditional plans, similar
to the GOLOG programming language. Within this logic, we can define the
expected utility of a conditional plan, based on the axiomatization of the
actions, the sensors and the utility. Sensors can be noisy and actions can
be stochastic. The planning problem is to find the plan with the highest
expected utility. This representation is related to recent structured
representations for partially observable Markov decision processes
(POMDPs); here we use stochastic situation calculus rules to specify the
state transition function and the reward/value function. Finally we show
that with stochastic frame axioms, action representations in probabilistic
STRIPS are exponentially larger than using the representation proposed
here.

Poscript file: http://www.ep.liu.se/ea/cis/1998/008/cis98008.ps

==========================================================================
2. Technical program of UAI-98
==========================================================================

Fourteenth Conference on Uncertainty in Artificial Intelligence

July 24-26, 1998
University of Wisconsin Business School
Madison, Wisconsin, USA

UAI'98 Conference Program

Joint COLT/ICML/UAI Reception
Conference and Course Registration
Thursday, July 23, 6:00-10:00 pm
Grainger Hall (Elwell Commons/Courtyard)

Friday, July 24, 1998

Conference and Course Registration
7:30-8:15 AM
First Floor Atrium, Grainger Hall

Welcome to Madison and Opening Remarks of the Collocated Conferences
8:15-8:30 AM
Jude Shavlik
Mills Concert Hall, Humanities Building

Joint COLT/ICML/UAI Invited Talk I
8:30-9:30 AM
Reinforcement Learning: How Far Can It Go?
Richard Sutton Introduction by Leslie
Pack Kaelbling
Mills Concert Hall, Humanities Building

Break 9:30-10:00 AM
First Floor Atrium, Grainger Hall

UAI Plenary Session I
10:00-11:40 AM
Session Chair: Kathryn B. Laskey
Room 1100 Grainger Hall (Morgridge Auditorium)

Utility Elicitation as a Classification Problem
Urszula Chajewska, Lise Getoor, Joseph Norman, and Yuval
Shahar Best Student Paper Award

Learning from What You Don't Observe
Mark A. Peot and Ross D. Shachter

Switching Portfolios
Yoram Singer

The Lumière Project: Bayesian User Modeling for Inferring the Goals and
Needs of Software Users
Eric Horvitz, Jack Breese, David Heckerman, David Hovel, and Koos Rommelse

Lunch 11:40 AM -1:30 PM
First Floor Atrium, Grainger Hall
Friday lunch ticket and UAI-98 Conference badge required please.

UAI Plenary Session II
1:30-3:10 PM
Session Chair: Peter Spirtes
Room 1100 Grainger Hall (Morgridge Auditorium)

On the Geometry of Bayesian Graphical Models with Hidden Variables
Raffaella Settimi and Jim Q. Smith

Graphical Models and Exponential Families
Dan Geiger and Christopher Meek

Bayesian Networks from the Point of View of Chain Graphs
Milan Studeny

Psychological and Normative Theories of Causal Power and the Probabilities
of Causes
Clark Glymour

Break 3:10-3:30 PM
First -Floor Atrium, Grainger Hall

UAI Poster Session: Overview of Presentations
3:30-4:05 PM
Session Chair: Ross D. Shachter
Room 1100 Grainger Hall (Morgridge Auditorium)

UAI Poster Session
4:05-6:30 PM
Room 5120 AB (Capitol Conference), Grainger Hall

A Hybrid Algorithm to Compute Marginal and Joint Beliefs in Bayesian
Networks and Its Complexity
Mark Bloemeke and Marco Valtorta

Marginalizing in Undirected Graph and Hypergraph Models
Enrique F. Castillo, Juan Ferrándiz, and Pilar Sanmartín

Dealing with Uncertainty in Situation Assessment: Towards a Symbolic
Approach
Charles Castel, Corine Cossart, and Catherine Tessier

Dynamic Jointrees
Adnan Darwiche

On the Semi-Markov Equivalence of Causal Models
Benoit Desjardins

Comparative Uncertainty, Belief Functions and Accepted Beliefs
Didier Dubois, Hélène Fargier, and Henri Prade

Inferring Informational Goals from Free-Text Queries: A Bayesian Approach
David Heckerman and Eric Horvitz

Any Time Probabilistic Reasoning for Sensor Validation
Pablo H. Ibargüengoytia, L. Enrique Sucar, and Sunil Vadera

Measure Selection: Notions of Rationality and Representation Independence
Manfred Jaeger

Dealing with Uncertainty on the Initial State of a Petri Net
Iman Jarkass and Michèle Rombaut

A Comparison of Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer
Architectures for Computing Marginals of Probability Distributions
Vasilica Lepar and Prakash P. Shenoy

Using Qualitative Relationships for Bounding Probability Distributions
Chao-Lin Liu and Michael P. Wellman

Magic Inference Rules for Probabilistic Deduction under Taxonomic Knowledge
Thomas Lukasiewicz

Lazy Propagation in Junction Trees
Anders L. Madsen and Finn V. Jensen

Constructing Situation Specific Belief Networks
Suzanne M. Mahoney and Kathryn Blackmond Laskey

Resolving Conflicting Arguments under Uncertainties
Benson Hin-Kwong Ng, Kam-Fai Wong, and Boon-Toh Low

Logarithmic Time Parallel Bayesian Inference
David M. Pennock

Context-Specific Approximation in Probabilistic Inference
David Poole

Planning with Partially Observable Markov Decision Processes: Advances in
Exact Solution Method
Nevin L. Zhang and Stephen S. Lee

Joint Reception, Banquet, and Invited Talk
7:00-9:30 PM
Madison Convention Center

Banquet Talk:
2.5 Millennia of Directed Graphs
David Spiegelhalter Introduction by
Steffen Lauritzen

----------------------------------------------------------------------------

Saturday, July 25, 1998

Conference and Course Registration
8:00-8:30 AM
First Floor Atrium, Grainger Hall

Joint COLT/ICML/UAI Invited Talk II
8:30-9:30 AM
Learning Agents for Uncertain Environments
Stuart Russell Introduction by Yishay
Mansour
Mills Concert Hall, Humanities Building

Break 9:30-10:00 AM
First Floor Atrium, Grainger Hall

UAI Plenary Session III
10:00-11:40 AM
Session Chair: Fahiem Bacchus
Room 1100 Grainger Hall (Morgridge Auditorium)

Tractable Inference for Complex Stochastic Processes
Xavier Boyen and Daphne Koller

Structured Reachability Analysis for Markov Decision Processes
Craig Boutilier, Ronen I. Brafman, and Christopher Geib

Flexible Decomposition Algorithms for Weakly Coupled Markov Decision
Problems
Ronald Parr

Hierarchical Solution of Markov Decision Processes Using Macro-actions
Milos Hauskrecht, Nicolas Meuleau, Leslie Pack Kaelbling, Thomas Dean, and
Craig Boutilier

Lunch 11:40 AM-1:15 PM
Rooms 3275 (Executive Dining Room) and 3180, Grainger Hall
Saturday lunch ticket and UAI-98 Conference badge required please.

UAI Invited Talk
1:15-2:15 PM
Treatment Choice in Heterogeneous Populations Using Experiments without
Covariate Data
Charles F. Manski Introduction by Greg
Cooper
Room 1100 Grainger Hall (Morgridge Auditorium)

UAI Panel Discussion
2:15-3:10 PM
Bayesian Network Interchange Format: A Dominated Option?
Panel Chairs: Bruce D'Ambrosio and Tod Levitt
Room 1100 Grainger Hall (Morgridge Auditorium)

Break 3:10-3:30 PM
First Floor Atrium, Grainger Hall

UAI Plenary Session IV
3:30-4:45 PM
Session Chair: Peter Haddawy
Room 2120 Grainger Hall (Kellner Auditorium)

Updating Sets of Probabilities
Adam J. Grove and Joseph Y. Halpern

Irrelevance and Independence Relations in Quasi-Bayesian Networks
Fabio Cozman

Merging Uncertain Knowledge Bases in a Possibilistic Logic Framework
Salem Benferhat and Claudio Sossai

Joint Poster Session: Overview of UAI Presentations
4:45-5:20 PM
Session Chair: Marco Ramoni
Room 2120 Grainger Hall (Kellner Auditorium)

Joint COLT/ICML/UAI/ILP Poster Session
7:00-8:00 PM Optional staffing of posters
8:00-9:30 PM Those posters staffed for which the first author's last
name is in A-L
9:30-11:00 PM Those posters staffed for which the first author's last
name is in M-Z
11:00-12:00 MN Optional staffing of posters
Madison Convention Center

This poster session will include UAI, COLT, ILP and ICML papers. See
COLT'98 , ICML'98 , and COLT'98
Conference Schedules for papers from the other conferences.

Each paper has a label assigned ([UAI-#] in the case of UAI papers). The
posters from all the conferences will be organized in alphanumeric order of
their labels.

UAI PRESENTATIONS

Note: Papers with an asterisk are both presented as plenary papers at UAI
and as posters at the joint poster session.

[UAI-1]
Tractable Inference for Complex Stochastic Processes (*)
Xavier Boyen and Daphne Koller

[UAI-2]
Empirical Analysis of Predictive Algorithms for Collaborative Filtering
John S. Breese, David Heckerman, and Carl Kadie

[UAI-3]
Query Expansion in Information Retrieval Systems using a Bayesian
Network-Based Thesaurus
Luis M. de Campos, Juan M. Fernández, and Juan F. Huete

[UAI-4]
Utility Elicitation as a Classification Problem (*)
Urszula Chajewska, Lise Getoor, Joseph Norman, and Yuval Shahar

[UAI-5]
The Bayesian Structural EM Algorithm (*)
Nir Friedman

[UAI-6]
Learning the Structure of Dynamic Probabilistic Networks
Nir Friedman, Kevin Murphy, and Stuart Russell

[UAI-7]
Learning by Transduction
Alex Gammerman, Vladimir Vovk, and Vladimir Vapnik

[UAI-8]
Graphical Models and Exponential Families (*)
Dan Geiger and Christopher Meek

[UAI-9]
Psychological and Normative Theories of Causal Power and the Probabilities
of Causes (*)
Clark Glymour

[UAI-10]
Minimum Encoding Approaches for Predictive Modeling
Peter Grünwald, Petri Kontkanen, Petri Myllymäki, Tomi Silander, and Henry
Tirri

[UAI-11]
Toward Case-Based Preference Elicitation: Similarity Measures on Preference
Structures
Vu Ha and Peter Haddawy

[UAI-12]
Solving POMDPs by Searching in Policy Space
Eric A. Hansen

[UAI-13]
Evaluating Las Vegas Algorithms -- Pitfalls and Remedies (*)
Holger H. Hoos and Thomas Stützle

[UAI-14]
An Anytime Algorithm for Decision Making under Uncertainty
Michael C. Horsch and David Poole

[UAI-15]
The Lumière Project: Bayesian User Modeling for Inferring the Goals and
Needs of Software Users (*)
Eric Horvitz, Jack Breese, David Heckerman, David Hovel, and Koos Rommelse

[UAI-16]
Hierarchical Mixtures-of-Experts for Exponential Family Regression Models
with Generalized Linear Mean Functions: A Survey of Approximation and
Consistency Results
Wenxin Jiang and Martin A. Tanner

[UAI-17]
Exact Inference of Hidden Structure from Sample Data in Noisy-OR Networks
Michael Kearns and Yishay Mansour

[UAI-18]
Large Deviation Methods for Approximate Probabilistic Inference
Michael Kearns and Lawrence Saul

[UAI-19]
Mixture Representations for Inference and Learning in Boltzmann Machines
Neil D. Lawrence, Christopher M. Bishop, and Michael I. Jordan

[UAI-20]
An Experimental Comparison of Several Clustering and Initialization Methods
Marina Meila and David Heckerman

[UAI-21]
A Multivariate Discretization Method for Learning Bayesian Networks from
Mixed Data
Stefano Monti and Gregory F. Cooper

[UAI-22]
Empirical Evaluation of Approximation Algorithms for Probabilistic Decoding
Irina Rish, Kalev Kask, and Rina Dechter

[UAI-23]
Decision Theoretic Foundations of Graphical Model Selection
Paola Sebastiani and Marco Ramoni

[UAI-24]
On the Geometry of Bayesian Graphical Models with Hidden Variables (*)
Raffaella Settimi and Jim Q. Smith

[UAI-25]
Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite
Information in Belief Networks and Influence Diagrams)
Ross D. Shachter

[UAI-26]
Switching Portfolios (*)
Yoram Singer

[UAI-27]
Bayesian Networks from the Point of View of Chain Graphs (*)
Milan Studeny

[UAI-28]
Learning Mixtures of DAG Models (*)
Bo Thiesson, Christopher Meek, David Maxwell Chickering, and David Heckerman

----------------------------------------------------------------------------

Sunday, July 26, 1998

Conference and Course Registration
8:00-8:30 AM
First Floor Atrium, Grainger Hall

Joint COLT/ICML/UAI Invited Talk III
8:30-9:30 AM

Conditional Independence: A Structural Framework for Uncertainty
Philip Dawid Introduction by Prakash P.Shenoy
Mills Concert Hall, Humanities Building

Break 9:30-10:00 AM
First Floor Atrium, Grainger Hall

UAI Plenary Session V
10:00-11:40 AM
Session Chair: Salem Benferhat
Room 1100 Grainger Hall (Morgridge Auditorium)

Axiomatizing Causal Reasoning
Joseph Y. Halpern

Qualitative Decision Theory with Sugeno Integrals
Didier Dubois, Henri Prade, and Régis Sabbadin

On the Acceptability of Arguments in Preference-Based Argumentation
Leila Amgoud and Claudette Cayrol

>From Likelihood to Plausibility
Paul-André Monney

Lunch 11:40 AM-12:45 PM (Note: There is an abbreviated lunch today.)
Rooms 3275 (Executive Dining Room) and 3180, Grainger Hall
Sunday lunch ticket and UAI-98 conference badge required please.

UAI Business Meeting: All are invited
12:45-1:30 PM
Room 1100 Grainger Hall (Morgridge Auditorium)

UAI Plenary Session VI
1:30-3:10 PM
Session Chair: John Mark Agosta
Room 1100 Grainger Hall (Morgridge Auditorium)

Flexible and Approximate Computation through State-Space Reduction
Weixiong Zhang

Incremental Tradeoff Resolution in Qualitative Probabilistic Networks
Chao-Lin Liu and Michael P. Wellman

Probabilistic Inference in Influence Diagrams
Nevin L. Zhang

Evaluating Las Vegas Algorithms - Pitfalls and Remedies
Holger H. Hoos and Thomas Stützle

Break 3:10-3:30 PM
First Floor Atrium, Grainger Hall

UAI Plenary Session VII
3:30-4:20 PM
Session Chair: Michael I. Jordan
Room 1100 Grainger Hall (Morgridge Auditorium)

Learning Mixtures of DAG Models
Bo Thiesson, Christopher Meek, David Maxwell Chickering, and David Heckerman

The Bayesian Structural EM Algorithm
Nir Friedman

Joint Panel Discussion
4:30-5:30 PM
Current Issues and Open Problems
Panel Chairs: Tom Dietterich, David Heckerman, and Michael Kearns
Mills Concert Hall, Humanities Building

----------------------------------------------------------------------------

Course on Uncertain Reasoning

Monday, July 27, 1998

Course Registration
7:00-8:10 AM
Outside 1100 Grainger Hall (Morgridge Auditorium)

Introduction and Goals
8:10-8:15 AM
Greg Cooper and Serafin Moral
Room 1100 Grainger Hall (Morgridge Auditorium)

Using Multi-Agent Systems to Represent Uncertainty
8:15-9:15 AM
Joseph Halpern
Discussion: 9:15-9:30 AM

Break 9:30-9:45 AM

Revising and Merging Uncertain Information: An Overview
9:45-10:45 AM
Henri Prade
Discussion: 10:45-11:00am

Partially Observable Markov Decision Processes
11:00-12:00 noon
Craig Boutilier
Discussion 12:00-12:15 PM

Lunch (On you own) 12:15-2:00 PM

Learning Causal Relationships from Observational Data
2:00-3:00 PM
Peter Spirtes and Richard Scheines
Discussion 3:00-3:15 PM

Discrete Optimization Problems for Inference in Bayesian Networks
3:15-4:15 PM
Dan Geiger
Discussion 4:15-4:30 PM

Break 4:30-4:45pm

The Application of UAI Technology and Methodology to Real-World Problems: A
Personal Perspective
4:45-5:45 PM
Kazuo Ezawa
Discussion 5:45-6:00 PM

==========================================================================
3. European Conference on Symbolic and Quantitative Approaches
to Reasoning with Uncertainty (ECSQARU'99)
First Call for Papers
==========================================================================

ECSQARU'99

5-9 July 1999

UCL, London, UK

http://www.cs.ucl.ac.uk/staff/a.hunter/ecsqaru

AIMS AND SCOPE
..............

Uncertainty is in an increasingly important research topic in many
areas of computer science. Many formalisms are being developed,
with much interest at the theory level directed at developing a better
understanding of the formalisms and identifying relationships between
formalisms, and at the technology level directed at developing software
tools for formalisms and applications of formalisms.

The main European forum for the subject is the European Conference
on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
(ECSQARU). These have been held in Marsellies (1991), Granada (1993),
Fribourg (1995), and Bonn (1997). The next in the series is ECSQARU'99
to be held in London in July 1999.

AREAS FOR CONTRIBUTION (not exclusive)
......................................

Default reasoning
Belief revision
Logics for reasoning with uncertainty
Paraconsistent logics
Belief functions
Bayesian networks
Probabilistic reasoning
Fuzzy systems
Aggregation of arguments
Inconsistency handling
Decision systems
Fusion systems
Argumentation systems
Applications of uncertainty formalisms
Automated reasoning systems for uncertainty
Machine learning for uncertainty

Theoretical results, algorithms, and applications that address the
the unification and integration of different approaches are
especially encouraged.

PROGRAM COMMITTEE
.................

Tony Hunter (London) - Program chair
Henri Prade (Toulouse) - Data fusion
Finn Jensen (Aalborg) - Bayesian networks
Torsten Schaub (Potsdam) - Default systems
Philippe Smets (Bruxelles) - Belief functions
Dov Gabbay (London) - Logics
Rudolf Kruse (Magdeburg) - Fuzzy methods

SUBMISSION OF PAPERS
....................


Please limit submissions to a maximum of 10 pages, preferrably
in LNCS format. Details on the LNCS format, including a Latex .sty
file, can be obtained from

www.springer.de/comp/lncs/index.html

To submit a paper, please send it as a postscript file by email, or
post four copies of it, to Tony Hunter at the following address:

Tony Hunter
Department of Computer Science
University College London
Gower Street
London WC1E 6BT
UK

Email: a.hunter@cs.ucl.ac.uk
Phone: +44 171 380 7295
Fax: +44 171 387 1397

PUBLICATION OF PROCEEDINGS
..........................

The proceedings will be published in the Lecture Notes in Computer
Science Series, as with all the previous ECSQARU conference
proceedings.

IMPORTANT DATES
...............

Submission deadline 31 January 1999

Notification of acceptance 12 March 1999

CRC for accepted papers 16 April 1999

Workshops and tutorials 5-6 July 1999

Main conference 7-9 July 1999


WORKSHOPS AND TUTORIALS
.......................

Additional workshops include:

- Fusion in data and knowledge

- Agents in an uncertain world

- Logic, uncertainty, and information retrieval

One-day introductory tutorials include:

- Bayesian networks

- Belief functions

- Default reasoning

If you are interested in adding to the workshop or tutorial programme,
please contact Simon Parsons (s.d.parsons@qmw.ac.uk).

FURTHER INFO
...............

For any other queries concerning the conference, please consult the
conference web page (www.cs.ucl.ac.uk/staff/a.hunter/ecsqaru)
or contact Tony Hunter.

:::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::

==========================================================================
4. Seventh International Workshop on Artificial Intelligence
and Statistics
Call for Papers
==========================================================================

January 3-6, 1999,
Ft. Lauderdale, Florida
http://uncertainty99.microsoft.com/

This is the seventh in a series of workshops which has brought
together researchers in Artificial Intelligence (AI) and in Statistics
to discuss problems of mutual interest. The exchange has broadened
research in both fields and has strongly encouraged interdisciplinary
work. Papers on all aspects of the interface between AI & Statistics
are encouraged.

To encourage interaction and a broad exchange of ideas, the
presentations will be limited to about 20 discussion papers in single
session meetings over three days (Jan. 4-6). Focused poster sessions
will provide the means for presenting and discussing the remaining
research papers. Papers for poster sessions will be treated equally
with papers for presentation in publications. Attendance at the
workshop will not be limited.

The three days of research presentations will be preceded by a
day of tutorials (Jan. 3). These are intended to expose researchers in
each field to the methodology used in the other field. The tutorial
speakers will include

Chris Bishop, Cambridge,
Latent variables and neural networks.
Sue Dumais, Seattle,
Information access and retrieval.

and the keynote speaker is

David Spiegelhalter, Cambridge, on
Bayesian statistical analysis.

Topics of Interest:

Statistics in AI:
vision, robotics, natural language processing, speech recognition
AI in statistics:
statistical advisory systems, experimental design
Automated data analysis
Cluster analysis and unsupervised learning
Integrated man-machine modeling methods
Interpretability in modelling
Knowledge discovery in databases
Learning
Metadata and the design of statistical data bases
Model uncertainty, multiple models
Multivariate graphical models, belief networks, causal modeling
Online analytic processing in statistics
Pattern recognition
Predictive modelling: classification and regression
Probabilistic neural networks
Probability and search
Statistical strategy
Visualization of very large datasets

This list is not intended to define an exclusive list of topics of
interest. Authors are encouraged to submit papers on any topic which
falls within the intersection of AI and Statistics.

Submission Requirements:

An extended abstract (up to 4 pages) should be emailed
(either ascii, word, postscript or a WWW address) to
joe.whittaker@lancaster.ac.uk
Telephone: +44 (0)1524 593960

or, as a last resort, four paper copies should be mailed to

Joe Whittaker Program Chair
7th International Workshop on AI and Statistics
Department of Mathematics and Statistics
Lancaster University, Lancaster, LA1 4YF, England

Submissions will be considered if they are received by midnight July
1, 1998. Please indicate which topic(s) your abstract addresses. Receipt
of all submissions will be confirmed via electronic mail. Acceptance
notices will be emailed by September 1, 1998.

Preliminary papers (up to 20 pages) must be received by November 1,
1998. These preliminary papers will be copied and distributed at the
workshop.

Program Chairs:
David Heckerman, Microsoft, heckerma@microsoft.com
Joe Whittaker, Lancaster University, joe.whittaker@lancaster.ac.uk

Program Committee:

Russell Almond, ETS, Princeton, ralmond@ets.org
Chris Bishop, Microsoft Research, Cambridge, cmbishop@microsoft.com
Wray Buntine, Thinkbank, Inc., wray@ultimode.com
Peter Cheeseman, NASA Ames, cheeseman@kronos.arc.nasa.gov
Max Chickering, Microsoft, dmax@microsoft.com
Paul Cohen, University of Massachusetts, cohen@cs.umass.edu
Greg Cooper, University of Pittsburgh, gfc@smi.med.pitt.edu
Phil Dawid, UC, London, dawid@stats.ucl.ac.uk
David Dowe, Monash University, David.Dowe@fcit.monash.edu.au
William DuMouchel, AT&T, dumouchel@research.att.com
Sue Dumais, Microsoft Seattle, sdumais@microsoft.com
David Edwards, Novo, DED@novo.dk
Doug Fisher, Vanderbilt University, dfisher@vuse.vanderbilt.edu
Nir Friedman, Berkeley, nir@cs.berkeley.edu
Dan Geiger, Technion, dang@cs.technion.ac.il
Edward George, University of Texas, egeorge@mail.utexas.edu
Clark Glymour, Carnegie-Mellon University, cg09@andrew.cmu.edu
David Hand, Open University, d.j.hand@open.ac.uk
Geoff Hinton, University of Toronto, hinton@ai.toronto.edu
Tommi Jaakkola, MIT, tommi@life.ai.mit.edu
Michael Jordan, Univ. California Berkeley, jordan@cs.berkeley.edu
Michael Kearns, AT & T , mkearns@research.att.com
Daphne Koller, koller@fiery.stanford.edu
Steffen Lauritzen, Aalborg University, steffen@math.auc.dk
Hans Lenz, Free University of Berlin, hjlenz@wiwiss.fu-berlin.de
David Lewis, AT&T Labs, lewis@research.att.com
David Madigan, University of Washington, madigan@stat.washington.edu
Andrew Moore, Carnegie-Mellon University, awm@cs.cmu.edu
Daryl Pregibon, AT&T Labs, daryl@research.att.com
Thomas Richardson, Univ. Wash, tsr@stat.washington.edu,
Alberto Roverato, Universita di Modena, roverato@unimo.it
Lawrence Saul, AT&T Labs, lsaul@research.att.com
Richard Scheines, Carnegie-Mellon University, rs2l+@andrew.cmu.edu
Sebastian Seung, Bell Labs, Lucent Technologies, seung@physics.lucent.com
Prakash Shenoy, University of Kansas, pshenoy@ukans.edu
Padhraic Smyth, JPL and UCI, smyth@sifnos.ics.uci.edu
David Spiegelhalter, MRC, Cambridge, david.spiegelhalter@mrc-bsu.cam.ac.uk
Peter Spirtes, Carnegie-Mellon University, ps7z@andrew.cmu.edu
Milan Studeny, Praha, studeny@utia.cas.cz
Nanny Wermuth, Mainz University, wermuth@animal.sowi.uni-mainz.de

==========================================================================
5. Conference on Information Processing and Management of
Uncertainty in Knowledge-based Systems - IPMU'98
Proceedings available - table of contents
==========================================================================

7th International Conference
IPMU'98
Information Processing and Management of
Uncertainty in Knowledge-based Systems

Paris, La Sorbonne
July 6-10, 1998

Proceedings of IPMU-98 (2 volumes, 2000 pages) can be ordered by sending
an email to Bernadette.Bouchon-Meunier@lip6.fr or to
Christophe.Marsala@lip6.fr. The price of the proceedings is 400 FF
(about 70$).

Table of contents / Table des matières

Programme
Possibility Theory / Théorie des Possibilités
Evidence Theory / Théorie de l'évidence
Statistics and Probabilities / Statistiques et probabilités
Envelopes for Detection and Prediction / Enveloppes pour la détection et la
prédiction
Fuzzy Preference Modeling and MCDM 1 / Modélisation floue des préférences
et décision
multicritère 1
Decision Models / Modèles décisionnels
Medical Applications of Fuzzy Sets / Applications médicales des ensembles flous
Fuzzy Quantities and their Processing / Quantités floues et leur traitement
Fuzzy Pattern Analysis / Reconnaissance des formes floues
Fuzzy Preference Modeling and MCDM 2 / Modélisation floue des préférences
et décision multicritère
2
Trees / Arbres
Chaos & Fractals 1
Databases / Bases de données
Fuzzy Control 1 / Commande floue 1
Ordinal Operations / Opérations ordinales
Decision Trees Under Uncertainty / Arbres de décision sous incertitude
Chaos & Fractals 2
Software Reusability 1 / Réutilisation de logiciels 1
Uncertainty in Geospatial Information Systems / Incertitudes dans les
systèmes d'information
géospatiaux
Fuzzy Control 2 / Commande floue 2
Aggregation Operators 1 / Opérateurs d'agrégation 1
Clustering /Regroupement
Software Reusability 2 / Réutilisation de logiciels 2
Military Applications / Applications militaires
Independence / Indépendance
Aggregation Operators 2 / Opérateurs d'agrégation 2
Information Processing in Medecine / Traitement d'informations en médecine
Learning / Apprentissage
Fuzzy Logic as a Basis for Knowledge Representation
in the Natural Science / Logique floue pour la représentation des connaissances
dans les sciences naturelles
Diagnostic et Fusion / Diagnostic and fusion
Probability and Logic of Fuzzy Sets / Probabilités et logique des ensembles
flous
Measures of Fuzziness and Entropy / Mesures de flou et d'entropie
Financial Risk 1 / Risque financier 1
Non-Standard Logics / Logiques non classiques
Techniques for Intelligent Information Processing / Techniques pour le
traitement intelligent
d'information
Rough Set Foundations & Methods 1 / Ensembles rugueux, fondements et méthodes 1
Fuzzy Measures 1 / Mesures floues 1
Financial Risk 2 / Risque financier 2
Non Classical Reasoning / Raisonnement non classique
Fuzzy Techniques / Techniques floues
Rough Set Foundations & Methods 2 / Ensembles rugueux, fondements et méthodes 2
Fuzzy Measures 2 / Mesures floues 2
Soft Computing
Causality / Causalité
Fuzzy Querying and Information retrieval over the Internet/WWW / Requêtes
floues et recherche
d'information sur Internet/WWW
Rough Set Applications / Applications des ensembles rugueux
Fusion
Fuzzy Petri Nets / Réseaux de Pétri flous
Classification and Recognition / Classification et reconnaissance
Traitement d'Incertitude / Uncertainty management
Information Measures and Probabilities/ Mesures d'information et probabilités
Connectives in Fuzzy Logic / Opérateurs de logique floue
Approximate Reasoning / Raisonnement approximatif
Artificial Intelligence / Intelligence artificielle
Uncertain Environment Management / Gestion d'environnement incertain
POSTERS / AFFICHES
Author index / Liste des auteurs

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