(text)
Jan Komorowski, ECAI-98 Workshop on Synthesis Of Intelligent Agent
Brighton, UK
(text)
Martin Kohler, CFP: PAKDD98-workshop on Parallel and Distributed Data Mining,
Melbourne, Australia, 15 April 1998 http://ruby.doc.ic.ac.uk/workshop/programme.html
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Readers of this mailing list may be interested in the following
article which was just published in JAIR:
Moore, A. and Lee, M.S. (1998)
'Cached Sufficient Statistics for Efficient Machine Learning with Large
Datasets', Volume 8, pages 67-91.
Available in PDF, PostScript and compressed PostScript.
For quick access via your WWW browser, use this URL: http://www.jair.org/abstracts/moore98a.html
More detailed instructions are below.
Abstract: This paper introduces new algorithms and data structures for
quick counting for machine learning datasets. We focus on the
counting task of constructing contingency tables, but our approach is
also applicable to counting the number of records in a dataset that
match conjunctive queries. Subject to certain assumptions, the costs
of these operations can be shown to be independent of the number of
records in the dataset and loglinear in the number of non-zero entries
in the contingency table.
We provide a very sparse data structure, the ADtree, to minimize
memory use. We provide analytical worst-case bounds for this structure
for several models of data distribution. We empirically demonstrate
that tractably-sized data structures can be produced for large
real-world datasets by (a) using a sparse tree structure that never
allocates memory for counts of zero, (b) never allocating memory for
counts that can be deduced from other counts, and (c) not bothering to
expand the tree fully near its leaves.
We show how the ADtree can be used to accelerate Bayes net structure
finding algorithms, rule learning algorithms, and feature selection
algorithms, and we provide a number of empirical results comparing
ADtree methods against traditional direct counting approaches. We
also discuss the possible uses of ADtrees in other machine learning
methods, and discuss the merits of ADtrees in comparison with
alternative representations such as kd-trees, R-trees and Frequent Sets.
The article is available via:
-- comp.ai.jair.papers (also see comp.ai.jair.announce)
The compressed PostScript file is named moore98a.ps.Z (122K)
-- automated email. Send mail to jair@cs.cmu.edu
or jair@ftp.mrg.dist.unige.it
with the subject AUTORESPOND and our automailer will respond. To
get the Postscript file, use the message body GET volume8/moore98a.ps
(Note: Your mailer might find this file too large to handle.)
Only one can file be requested in each message.
For more information about JAIR, visit our WWW or FTP sites, or
send electronic mail to jair@cs.cmu.edu
with the subject AUTORESPOND
and the message body HELP, or contact jair-ed@ptolemy.arc.nasa.gov. Previous2NextTop
Date: Tue, 31 Mar 1998 11:04:12 -0600
From: jones@cis.uab.edu
(Warren Jones)
Subject: CFP: ACM SIGBIO Newsletter: Biomedical Knowledge Discovery
and Data Mining
Web: http://sigbio.cis.uab.edu
A special issue of the Association for Computing Machinery Special Interest
Group on Biomedical Computing (ACM SIGBIO) Newsletter is being planned. This
issue will be a collection of short descriptions of projects which are applying
knowledge discovery and data mining techniques to the health and biological
sciences. The goal of this special issue is to identify as many projects as
possible and thus the community in this area. A form for submitting information
is available at URL: http://sigbio.cis.uab.edu.
Please submit by June 30, 1998.
Contact: Warren T. Jones, Editor of Special Issue
Department of Computer and Information Sciences
University of Alabama at Birmingham
Birmingham, AL 35294-1170
Email: jones@cis.uab.edu
Fax: (205) 934-5473
Phone: (205) 934-2213
'There have been some great new KDD developments recently, but I can see
that there are still many ways that faster, more reliable and completely
objective data mining and knowledge discovery can be achieved. Some
readers will remember the early progress of SuperInduction, last year.
This up-dated version http://www.hal-pc.org/~jpbrown
(much more to
come) shows that the path to perfection is being hotly pursued.'
Previous4NextTop
From: Aviva.Lev-Ari@ps.net
Date: Fri, 27 Mar 1998 10:56:00 -0600
Subject: Applied Research Position in Kendall Square, Cambridge, MA
I would like to explore the possibility of interviewing candidates
with academic background in the following Quantitative/Modeling
domains:
- Statistics
- Mathematics
- Operations Research
- Computer Science - numerical analysis
- Econometrics
- Psychometrics
Applied Research Employment opportunity for MSc or Ph.D. level.
- Internet Economics
- Electronic Commerce Transaction Information Analytics
- Data Mining
- Network performance analysis
- Online shopping behaviour
- Organizational ecology (mathematical sociology)
- Supply chain modeling
Candidate shall master some not all of the above areas.
Profile:
To fit an interdisciplinary team of extremely bright professionals,
creative and inquisitive young broadly trained in Quantitative Methods
and Measurement Theory with an undergrade education in
Stat/Math/OR/CS/Econometrics/Psychometrics.
Modifyable into an independent applied researcher and heavy user of
S-Plus, SAS, Mathematica, MatLab, LaTex and graphical software.
Excellent writing (technical editorial skills) and oral communication
skills (ability to explain technical terms to non-technical
professionals). Independent in exploration of newly research concepts
assigned to, offer creative ideas to the project, and amenable to be
mentored and expand his/hers knowledge boundaries on a daily basis.
A team player, substantiated professional confidence desirable,
highest integrity with handling data, choosing methods and respecting
the technical savvy of other peers and management.
Position to be filled by June 1998.
Compensation:
Master Level: up to $45K - $60K
Ph.D. Level: up to $60K - $80K
Benefits and stock options.
Contact:
Aviva Lev-Ari, Ph.D.
Director of Information Analytics
TimeO Group, Electronic Commerce Division of PSC
Perot Systems Corp (PSC)
101 Main St.
Cambridge, MA 02142
(617) 303-5011
e-Mail: Aviva.Lev-Ari@ps.net Previous5NextTop
From: Christophe Giraud-Carrier cgc@cs.bris.ac.uk
Subject: MSc in ML at Bristol
Date: Mon, 23 Mar 1998 21:25:13 +0000 ()
The Department of Computer Science at the University of
Bristol (UK) offers a MSc in Machine Learning. Bristol is
one of the UK's most active research centres in Machine
Learning, with Prof John Lloyd, Dr Peter Flach, Dr
Giraud-Carrier and currently 5 research assistants/students.
----------------------
Christophe Giraud-Carrier, Lecturer in Computer Science
University of Bristol
Department of Computer Science
Merchant Venturers Building
Woodland Road
Bristol, BS8 1UB
United Kingdom Previous6NextTop
Date: Fri, 27 Mar 1998 11:59:13 +0100 (MET)
From: Yves.Kodratoff@lri.fr(Yves.Kodratoff@lri.lri.fr)
Subject: French Petroleum Institute Position in Lyon, France
The French Petroleum Institute, a world-class research center on petroleum
and its applications, is looking for PhD candidates *** from the European
Community *** in data mining for its Industrial Development Center in
Solaize near Lyon, France.
The theoretical body of the thesis will be to work on deviation detection
and outliers inspection in data bases containing continuous variables. The
application concerns IFP data bases in refining and petrochemicals, namely
: automated clustering of feedstock and products, applied outlier
detection, and looking for relationship between the design and operations
parameters.
The work will be supported by up-to-data scientific computing means
including software and workstations/PC.
A grant of more than 8000 FF a month the first year, 9000 FF the
second, and 10000 FF the third is proposed (net salary).
Candidates should prepare : - a cv, - two recommendation letters, -
a motivation letter
and send them by mail or e-mail to
Francois WAHL, Institut Francais du Petrole, BP3, F - 69390 VERNAISON
e-mail : Francois.WAHL@IFP.fr
Previous7NextTop
Date: Fri, 3 Apr 1998 12:12:06 -0500
From: Eric King, eric@heuristics.com
Subject: Data Mining Two Day Course with Workshop
Web: May 11 and 12 Herndon, VA
==================DATA MINING: PRINCIPLES AND PRACTICE=================
| offered by - The Gordian Institute |
| May 11 and 12 Herndon, VA $995 |
------------------------------------
Whether you are new to the complex science of data mining, or have already
realized its elusive paths to success, a two day course offered by The
Gordian Institute entitled 'Data Mining: Principles and Practice' will
provide an intensive introduction to the process of data mining. Those in
attendance will learn about different methods of modeling and how those
models apply to real business problems.
'Data Mining: Principles and Practice' is designed to offer thorough
reviews of terminology, as well as benefits and pitfalls of the technology
while minimizing time away from the office. The two day data mining
seminar covers the subject of data mining from the ground up. The key
issue explored in this short course is how to avoid frustrating and costly
mistakes and improve your business process by correct use of these powerful
methods.
ATTENDEES WILL LEARN:
- The basic principles and terminology of data mining
- The different methods of data mining and how they compare
- How to prepare raw data for data mining
- How to analyze and validate the results
- What questions data mining can answer
- What are the pitfalls and how to avoid them
- What commercial products are available and how to evaluate them
Gordian's 'Data Mining: Principles and Practice' seminar focuses on actual
use and implementation of data mining techniques in the real world. The
instructor has been deeply involved with the development of data mining
methods and the means of their use. Actual products will be reviewed, as
will results drawn from real data mining applications.
OPTIONAL THIRD-DAY HANDS-ON WORKSHOP
Those who would like a hands-on perspective to the instructional sessions
may attend an optional third day application workshop for an additional
$495. The workshops will highlight superior performance as well as
pitfalls resulting from various tools and techniques when applied to
different types of data intensive problems. Exercises will reveal
impressive results from the same technique that may have failed in another
category.
In addition, objective evaluations of popular data mining products can save
immeasurable time and effort in assessing and selecting which suite of
tools will perform best for your application. The Gordian Institute is not
a data mining tools company. Data mining methods, tools and products will
be presented objectively. The instructor will show how to evaluate various
packages based on strengths, limitations, value and general performance.
Products will be separated into four categories:
- Statistical
- Decision Tree
- Neural Net
- Clustering Technologies
GORDIAN INSTITUTE'S QUARTERLY NEWSLETTER
The next offering of 'Data Mining: Principles and Practice' will be
presented May 11 and 12 in Herndon, VA (DC Metro Area) at $995. If the
venue of the next offering is not suitable, a free subscription to
Gordian's quarterly newsletter will include announcements of future
offerings in addition to informative articles related to intelligent
software solutions. To subscribe, simply send an empty Email message with
'Gordian's Quarterly Newsletter' in the subject to agent@gordianknot.com
THE PRESENTER
Ben A. Hitt, Ph.D. has many years of experience using pattern recognition
technologies and intelligent software tools to solve business problems. He
has taught thousands of students in the use and principles of advanced
software and machine learning technologies. He was Director of Training
for NeuralWare, Inc. in Pittsburgh, PA, and in that role instructed the use
of neural networks for Financial Forecasting, Fraud Detection, Process
Control and Direct Marketing. He was instrumental in the design and
development of ModelMAX, a complete neural network application for the
direct marketing industry. Dr. Hitt also designed and implemented a
nationally recognized detection system for rapid tax refund application
fraud. He has recently conducted a detailed and exhaustive survey of
commercial data mining products for a major US bank.
REQUEST FULL DETAILS
Reserve your seat early, as course sizes are limited to allow for a high
level of interaction with the instructors. You may request details for
this course, to include pricing, specific dates, course outline, site
logistics and registration form through any of the following:
______________________________________________
- Email: agent@gordianknot.com
(Reply with either or both as the SUBJECT)
- Data Mining Details
- Gordian's Quarterly Newsletter
- Web: http://www.gordianknot.com
- Toll Free: 800-405-2114
- Direct: 281-364-9882
- Fax: 281-754-4014
______________________________________________
Workshop: Keys to the Commercial Success of Data Mining
To be held in conjunction with The Fourth International Conference on
Knowledge Discovery and Data Mining
New York City, August 31, 1998 http://www.aaai.org/Conferences/KDD/1998/
Chairs:
Kurt Thearling
Director of Advanced Analytics
Exchange Applications
695 Atlantic Avenue
Boston, MA 02111
Roger M. Stein
Vice President, Senior Credit Officer
Quantitative Analytics and Knowledge Based Systems
Moody's Investors Service
99 Church Street
New York, NY 10007
Data mining is on the cusp of true commercial success. Commercial
institutions are starting to move beyond pilot studies and research programs
toward the production use of predictive models for real world business
applications. While this is exciting, it is also where it gets harder.
Successful data mining in business doesn't come down to simply having a hot
algorithm and giving it to an experienced modeler. Business users care
about things such as database support, application integration, business
templates, flexibility, scalability, real profitability, and other issues
that have not historically been the concern of the KDD community.
From a development point of view, the core algorithms are now a small part,
perhaps 10%, of the overall data mining application, which itself is only
10% of the business process that contains the application. The purpose of
this workshop is to focus on the remaining 99% so that commercial data
mining application are relevant to business users.
The goal is to bring together a diverse group of developers, users, and
integrators of business data mining applications. The workshop will
consist of a number of in-depth case studies and analyses, several invited
speakers, and panel sessions. Time will also be set aside for
discussions.
It is expected that the workshop will include forty to fifty participants.
for full details and submission guidelines see the web site above.
Timetable:
Jun 15: Papers due
Jul 10: Notification of acceptance/rejection
Aug 31: Workshop
CALL FOR PAPERS: Workshop on DISTRIBUTED DATA MINING
The Fourth International Conference on Knowledge Discovery and Data Mining
New York City, August 31, 1998
CHAIRS:
Hillol Kargupta
Faculty of Computer Science
School of Electrical Engineering and Computer Science
Washington State University
Pullman, WA 99164-2752
e-mail: hillol@eecs.wsu.edu
Philip Chan
Computer Science
Florida Institute of Technology
150 W. University Blvd.
Melbourne, FL 32901
email: pkc@cs.fit.edu
PROGRAM COMMITTEE:
David Levine, Boeing Corporation
Foster Provost, Bell Atlantic
Jiawei Han, Simon Fraser University
Michael Huhns, University of South Carolina
Ron Musick, Lawrence Livermore Laboratory
Salvatore Stolfo, Columbia University
Vincent Ng, Hong Kong Polytechnic University
William Cohen, AT&T Labs Research
Zoran Obradovic, Washington State University
WORKSHOP DESCRIPTION AND OBJECTIVES:
Automated detection of patterns from large amount of data is often called
data mining. As computing and communication are increasingly converging to
each other, mining data, stored in distributed databases with adequate
attention to security related issues, is of growing interest. Distributed
data mining (DDM) systems are finding an increasing number of applications
in popular Intranet/Internet environments, data mart based warehousing
architectures, network intrusion detection, geographical information
systems and many others. This workshop will provide a platform for
discussing theoretical and applied research issues in DDM. The topics
of interest include, but are not limited to:
1) Theory and foundation issues in DDM: Problem decomposability and data
distribution; complexity issues in DDM; representational issues.
2) Methods and algorithms: Distributed algorithms for popular data mining
techniques (e.g. association rules, classifiers, clustering);
techniques for communication minimization, cooperative learning.
3) Software agents and DDM: Agent based approaches in DDM.
Agent interaction: cooperation, collaboration, negotiation,
organizational behavior
4) DDM for spatial data: DDM in geographical information databases
5) Architectural issues in DDM: Architecture, control, security,
communication issues
6) Experimental DDM systems: Large experimental systems, performance,
design issues.
7) Applications of DDM: Application of DDM in business, science,
engineering, and medicine.
8) Human interaction in DDM: Human-DDM interface, multi-user interaction
in DDM.
9) Distributed data mining on the Internet
10) Parallel Data mining: Parallel data mining algorithms, applications;
high performance computing in DDM
CALL FOR ABSTRACTS:
SIGMOD'98 Workshop on Research Issues in
Data Mining and Knowledge Discovery (SIGMOD-DMKD'98)
Seattle, Friday, June 5, 1998
=================================================================
OBJECTIVES
Data Mining and Knowledge Discovery has become an active area of
research, attracting people from several disciplines: database
systems, AI, machine learning, statistics, information retrieval, and
data visualization. Data mining products and toolkits are now
commercially available, and serious industrial applications are being
developed. There are several interdisciplinary conferences on the
topic of data mining. The Workshop on Research Issues in Data Mining
and Knowledge Discovery (DMKD) was started two years ago as a forum for
database researchers to discuss issues related to data mining from
large databases and data warehouses. The first two workshops were held
in conjunction with SIGMOD/PODS 1996 and 1997, and were successful in
attracting a large number of participants. These two workshops focused
primarily on advances in data mining algorithms and techniques. These
topics have now become standard fare in the programs of leading
database conferences. Therefore, we have chosen to emphasize a
somewhat different theme for this year's workshop. Our objective is to
bring together researchers and practitioners to discuss research
issues and experience in developing and deploying data mining systems,
applications, and solutions.
FORMAT
The workshop will be held the day following the SIGMOD /PODS'98
conference. We expect about half a day to be devoted to technical
presentations based on accepted papers. The program will also include
several invited speakers from industry who will share their experience
in developing and deploying data mining technology, and there will be
time to discuss issues related to building data mining systems.
May Day for Missing Data!
The Chicago Chapter of the American Statistical Association is pleased to
announce a conference on Statistical Analysis with Missing Data to be held
on May 1, 1998. Invited speakers include Rod Little (University of
Michigan), Joe Schafer (Penn State University), Nancy Cook (Harvard Medical
School), and David Judkins(Westat, Inc.). Additionally, representatives
from software companies
SOLAS and SPSS will present use of their programs for missing data. For
more information contact Don Hedeker (312-996-4896; hedeker@uic.edu)
or
consult the chapter website at http://www.ChicagoASA.org/.
|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
| LYND BACON & ASSOCIATES, LTD. http://www.lba.com
|
| marketing and management science mr.daemon@lba.com
|
| Homewood IL USA +1.708.957.0883 |
| --------------------- |
| Find out about the Chicago ASA monthly speaker series |
| at http://www.lba.com/asa-lunch.html
|
/////////////////////////////
*** ADVANCED BLACK-BOX TECHNIQUES FOR NONLINEAR MODELING:
THEORY AND APPLICATIONS ***
Date: July 8-10, 1998
Place: Katholieke Universiteit Leuven, Belgium
On-line Info: http://www.esat.kuleuven.ac.be/sista/workshop/
Organized at the Department of Electrical Engineering (ESAT-SISTA) and the
Interdisciplinary Center for Neural Networks (ICNN) in the framework of the
project KIT and the Belgian Interuniversity Attraction Pole IUAP P4/02.
In cooperation with the IEEE Circuits and Systems Society.
SGES: the Specialist Group on Knowledge-Based Systems and Applied
Artificial Intelligence
ES98: Cambridge, England, December 14th-16th 1998
Call for Contributions
The 18th SGES International Conference on Knowledge-Based Systems and
Applied Artificial Intelligence is being held in Cambridge between
14th and 16th December 1998.
The objective of the annual SGES conferences is to bring together
researchers and application developers from business, industrial and
academic communities to discuss issues and solutions to problems based
on techniques derived from Artificial Intelligence.
These conferences are the premier European forum for Applied AI. The
two-day conference (December 15th-16th) will be preceded by a day of
tutorials on AI topics. The whole event will be accompanied by an
exhibition.
The Conference continues to build on the success of previous years,
with a two-track event containing fully refereed technical and
applications papers.
For the Technical Stream, contributions are invited in the form of
papers of up to 5,000 words presenting original work on
knowledge-based systems or other areas of Artificial Intelligence.
Areas of interest include (but are not restricted to): knowledge-based
systems, knowledge engineering methodology, constraint satisfaction,
intelligent agents, machine learning, model-based reasoning,
verification and validation of KBS, natural language understanding,
case-based reasoning, neural networks, genetic algorithms, data mining
and knowledge discovery in databases.
For the Application Stream, contributions are invited in the form of
papers of up to 5,000 words presenting case studies of knowledge-based
or other AI systems that address real-world problems such as
diagnosis, monitoring, scheduling and selection. Most importantly, the
papers should highlight the critical elements of success and the
lessons learned.
IMPORTANT DATES:
Title/Abstract notification: now
Full paper submission: 19 June 1998
Notification of acceptance: 7 August 1998
Camera ready papers due: 18 September 1998
Previous14NextTop
Date: Tue, 24 Mar 1998 23:32:54 +0100
From: Jan Komorowski janko@control.lth.se
Subject: ECAI Workshop on Synthesis Of Intelligent Agent
Synthesis Of Intelligent Agent Systems From Experimental Data
A Workshop at ECAI'98, Brighton, UK
Organizing Committee: Jan Komorowski, Norway/Sweden, Chair; Ivo
Duentsch, North Ireland, Andrzej Skowron, Poland
ABSTRACT
Two major questions arise in the analysis and synthesis of the behavior
of intelligent agents:
- how an intelligent agent discovers decision rules from
experimental data,
- what is a general framework for approximate reasoning about
teams of intelligent agents.
We invite submission of original papers (up to 10 pages) reporting on
research in progress that investigates applications of approximate
reasoning techniques to synthesis of intelligent agents. The papers
will be reviewed by the the workshop organizing committee.
Approximately 8 papers will be selected for full presentation at the
workshop; all other papers judged to be of sufficiently high quality
will be accepted for publication in the proceedings of the workshop.
(For style guidelines see http://www.cogs.susx.ac.uk/ecai98/style.html
Much attention has recently focused on rough sets, Boolean reasoning
techniques and rough mereology as appropriate techniques for answering
several of the above questions. During the workshop we wish to
investigate these and related approaches such as, for instance,
case-based, statistical, modal and multi-valued logics and logic
programming applied to the problem of synthesis from experimental
data. Theoretical, applied and comparative work will be considered.
After the workshop, the authors will be invited to submit revised and
full versions of their papers to be evaluated for a collected
publication.
Workshop participation is limited to 30 people. Priority will be given
to authors of the submitted papers. All participants must register for
ECAI98.
About four central topics will be introduced by invited experts in the
field. Abstracts of their presentations will be posted on the web in
January 1998.
Important dates:
Submission of the papers: 3 April 1998
Notification of acceptance: 11 May 1998
Camera ready papers: 1 June 1998
Submissions are to be sent to skowron@mimuw.edu.pl
(postscript files)
or s-mailed to Prof. Andrzej Skowron, Department of Mathematics,
Warsaw University, ul. Banacha 2, 02 097 Warsaw, POLAND. Electronic
submissions are preferred.
The PAKDD Workshop on Parallel and Distributed Data Mining (PDDM-98)
Melbourne Convention Centre, Melbourne, Australia
15 April 1998
The workshop is associated with The Second Pacific-Asia Conference on
Knowledge Discovery and Data Mining (PAKDD-98)
Data mining is the automatic discovery of patterns, changes,
associations and anomalies in large data sets. Data mining is
emerging as a key enabling technology for a variety of scientific,
engineering, medical and business applications. This workshop will
focus on three key issues:
1. Scaling data mining algorithms, applications and systems to massive
data sets. The workshop will highlight techniques from high
performance and parallel computing and their applications to data
mining.
2. Developing data mining algorithms, applications and systems for
mining distributed data. The workshop will highlight distributed data
mining and distributed data intensive decision support.
3. Integrating data mining with other systems and applications to
support business processes throughout large enterprises.
This workshop aims to bring together researchers working on all
aspects of parallel and distributed data mining during the PAKDD 98
conference. The workshop is scheduled for one day and includes
presentations and discussions. Please check the advance programme of
the workshop for details:
The workshop proceedings will be published by either World Scientific
or Imperial College Press, UK. Selected papers from the workshop will
be published in a special issue of the Journal of Data Mining and
Knowledge Discovery.
We would like to welcome you to participate in the PDDM-98 workshop.
Please check the registration details at:
Knowledge Discovery Nuggets Index