Machine Learning List
Mon, 17 Mar 2003 21:30:37 -0800
Machine Learning List: Vol. 15, No. 5
Monday, Mar 17, 2003
Contents
Calls for Papers and Other Meeting Announcements
Call for papers - Special session on Learning Soccer Agents (SMC'03)
Cognitive Science conference, Sydney July 13-17
DATE CHANGE: Workshop on Advances in Machine Learning, June 8-11, 03
Career Opportunities
Machine learning job openings at RIACS/NASA Ames
PhD Studenship Offer
Misc Other Announcements
clustering of all Machine Learning in Medicine articles
SIGKDD Explorations Volume 4, Issue 2 available online
The Machine Learning List is moderated. Contributions should be
relevant to the scientific study of machine learning. Please send
submissions for distribution to: [EMAIL PROTECTED] For requests to be
added, removed, or to change your email address, send email to:
[EMAIL PROTECTED]
In general, submissions should be no more than a few full-screens of
text. For meeting announcements, highlight the conference or workshop
web page and give a summary description of the goals of the event.
Information such as the list of program committee members, talk
schedules, and registration forms are unnecessary and should not be
included. Job adds are usually no more than a few full-screens so
they should fit naturally.
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From: "Tomoharu Nakashima" <[EMAIL PROTECTED]>
Subject: Call for papers - Special session on Learning Soccer Agents (SMC'03)
Date: Tue, 4 Mar 2003 05:37:59 +0900
CALL FOR PAPERS
Special Session on Learning Soccer Agents
IEEE International Conference
on Systems, Man, and Cybernetics (SMC'03)
https://becat.engr.uconn.edu/IEEE_CSMC_2003/
We are organizing a special session in the IEEE International
Conference on Systems, Man, and Cybernetics (SMC'03). The theme of
the special session is "Learning Soccer Agents".
The scope of this special session is to present papers that apply a
learning method to soccer agents (either hardwares or softwares).
Examples of the research topics include, but are not limited to:
Multi-agent systems,
Distributed autonomous systems,
Machine learning (Decision trees, rule-based systems, etc.),
Neural networks,
Evolutionary computation,
Fuzzy systems,
Reinforcement learning,
Statistical learning theory, and
Game theory.
We would like to invite you (or a member of your group) to contribute
a paper for this session. If you are interested, please send the
followings to me ([EMAIL PROTECTED]) as soon as possible:
(1) The title,
(2) The author(s) and affiliation(s),
(3) The corresponding author's contact information
(E-mail address, postal address, and phone & FAX numbers), and
(4) One-page abstract (pdf format).
IMPORTANT DAYS
April 5, 2003: One-page abstract submission due
May 5, 2003: Acceptance notification
June 23, 2003: Camera-ready paper submission due
Although five papers are expected to be included in the special session,
we can accomodate more papers to form a special 'track' on the theme.
------------------------------
From: Peter Slezak <[EMAIL PROTECTED]>
Subject: Cognitive Science conference, Sydney July 13-17
Date: Sat, 8 Mar 2003 12:58:08 +1100
Announcement and Call for Papers
COGNITIVE SCIENCE
Joint International Conference
4th ICCS International Conference on Cognitive Science
7th ASCS Australasian Society for Cognitive Science Conference
13-17 July, 2003
The University of New South Wales
Sydney, Australia
http://www.cogsci.unsw.edu.au
DEMONSTRATION
Sony Legged Robots
'ROBOCUP' 2001, 2002 World Champion UNSW Team
SUBMISSIONS
We invite submissions from all disciplines within Cognitive Science,
including:
Computer science & Artificial Intelligence
Linguistics
Neuroscience
Philosophy
Psychology
Anthropology
Submissions for papers and posters will be reviewed on the basis of
abstracts accepted via our website: http://www.cogsci.unsw.edu.au
IMPORTANT KEY DATES
*Please note: In case early notice of acceptance is needed, we will
provide rapid response to submissions made at any time earlier than
the deadlines below:
1 April 2003 Abstracts and proposals for symposia due
1 May 2003 Notice of acceptance or rejection
1 June 2003 Full papers due
13-17 July, 2003 Conference
Proposals are invited for special streams and symposia. Planned
symposia include:
* Music and Cognition
* Mental Representation
* Cognitive Science and Education
* Cognitive Science of Science
* Animal Cognition
* Decision Making, Risk & Behavioural Finance
* Language and Cognition
* Brain imaging
* Machine Learning
* Evolutionary psychology
* Historical Foundations of Cognitive Science
* Psychiatry, Neuropsychiatry & Psychoanalysis
Submission of proposals for symposia and workshops should be emailed
to Peter Slezak: [EMAIL PROTECTED]
------------------------------
From: Balazs Kegl <[EMAIL PROTECTED]>
Subject: DATE CHANGE: Workshop on Advances in Machine Learning, June 8-11, 03
Date: Fri, 14 Mar 2003 12:19:21 -0500
An unfortunate coincidence with the Formula-1 race in Montreal (Grand
Prix) forces us to shift the Workshop on Advances in Machine Learning
from June 9-13 to June 8-11. If you plan to come and you need
accommodation, please mail to our local organizer, Louis Pelletier
([EMAIL PROTECTED]) the earliest possible (hotels are filling
up quickly because of the car race even before the 12th).
We apologize for the inconvenience the repeated date change may
cause. The paper submission deadline remains March 31.
Call for papers
Workshop on Advances in Machine Learning
Montreal, Canada, June 8-11, 2003
URL: www.iro.umontreal.ca/~lisa/workshop2003.html
SCOPE:
Probabilities are at the core of recent advances in the theory and
practice of machine learning algorithms. The workshop will focus on
three broad areas where these advances are crucial: statistical
learning theory, learning algorithms, and reinforcement learning. The
workshop will therefore bring together experts from each of these
three important domains. Among the sub-topics that will be covered, we
note: variational methods, graphical models, the curse of
dimensionality, empirical methods to take advantage of theories of
generalization error, and some of the applications of these new
methods.
On the theoretical side, in recent years a lot of effort has been
devoted to explain the generalization abilities of popular learning
algorithms such as voting classifiers and kernel methods. Some of
these results have given rise to general principles that can guide
practical classifier design. Some (non-exclusive) sub-topics in this
aspect of the workshop include Rademacher and Gaussian complexities,
algorithmic stability and generalization, localized complexities and
results on the generalization ability of voting classifiers and
kernel-based methods.
On the algorithmic side, one of the emphasis of recent years has been
on probabilistic models that attempt to capture the complex structure
in the data, often by discovering the main lower-dimensional features
that explain the data. This raises interesting and difficult questions
on how to train such models, but such algorithms may have wide ranging
applications in domains in which the data has interesting structure
that may be explained at multiple levels, such as in vision and
language.
In reinforcement learning (RL), recent research has brought
significant advances in some of the traditional problems, such as
understanding the interplay between RL algorithms and function
approximation, and extending RL beyond MDPs. At the same time, new
areas of research, such as computational game theory, have developed
at the interface between RL and probabilistic learning methods. In
this workshop, we invite presentations on all RL topics, ranging from
theoretical development to practical applications.
IMPORTANT DATES:
March 31, Paper submission deadline
April 15, Notification of paper acceptance/rejection.
------------------------------
From: "Serdar Uckun" <[EMAIL PROTECTED]>
Subject: Machine learning job openings at RIACS/NASA Ames
Date: Tue, 4 Mar 2003 09:05:51 -0800
RIACS and NASA Ames Research Center have four job openings for
research scientists in the area of Machine Learning with applications
in NASA's strategic enterprises.
The Research Institute for Advanced Computer Science (RIACS) performs
computer science research in collaboration with NASA and university
scientists to solve challenging scientific problems in support of
NASA's goals and missions. RIACS is located at NASA Ames Research
Center in the heart of Silicon Valley. RIACS is an institute of the
Universities Space Research Association (USRA), a non-profit
organization. See http://www.riacs.edu for further details.
The existing openings are:
Senior Scientist - Machine Learning
Synopsis: R&D in machine learning and data mining; 10 years experience.
Job ID: 03-04
Posted: February 12, 2003
Location: Moffett Field, CA
Senior Scientist - Machine Learning and Space Sciences
Synopsis: R&D in machine learning and data mining; space science
background; 5 years experience.
Job ID: 03-05
Posted: February 18, 2003
Location: Moffett Field, CA
Senior Scientist - Bioinformatics
Synopsis: R&D in bioinformatics; strong computer science background; 5
years experience.
Job ID: 03-06
Posted: February 18, 2003
Location: Moffett Field, CA
Scientist - Bioinformatics and Machine Learning
Synopsis: R&D in bioinformatics; strong computer science and machine
learning background; 2 years experience.
Job ID: 03-09
Posted: February 18, 2003
Location: Moffett Field, CA
See http://www.riacs.edu/employment for further details on these
positions and instructions on how to apply.
------------------------------
From: Armando Vieira <[EMAIL PROTECTED]>
Subject: PhD Studenship Offer
Date: Mon, 10 Mar 2003 23:55:45 +0000
A PhD Studentship position for a period of three years is open in
Polymer Department at University of Minho, Guimar=E3es, to work on
Multiobjective optimisation with evolutionary algorithms using Neural
Networks. The objective of the work is to study and develop new
methods to increase the performance of Genetic Algorithms in
multi-optimization problems through the use of Artificial Neural
Networks to speed the search of useful solutions. The work will be
applied to the important problem of polymer extrusion.
This work uses new and fascinating topics linking concepts from
biology, physics and machine learning. The work developed will
therefore have a great potential to open new frontiers with a high
impact on the scientific community. The candidate will integrate a
young and dynamic team with several years of expertise with an active
publication record in international referee journals. The Polymer
Department has a well established and active research team with
several PhD and first quality facilities.
The work will take place in the modern Azurem campus at Guimar=E3es,
with excellent working conditions including computer facilities and
access to bibliography. Guimar=E3es is a beautiful historic city at
the heart of the exuberant Minho province, north of Portugal,
classified by UNESCO as World Patrimony. Although a small and relaxing
city, Guimar=E3es has an important student community that brings its
streets full of live.
Profile required: Bachelor or Master in Physics, Material Science or
Computer Science with knowledge programming on C language and good
analitic skills.
Project supervisors: Prof. Ant=F3nio Gaspar-Cunha and Armando Vieira.
Submissions Deadline: 15 April
For more information contact A. Gaspar:
Phone: +351 253 510328
[EMAIL PROTECTED]
http://www.dep.uminho.pt=20
------------------------------
From: Raul Valdes-Perez <[EMAIL PROTECTED]>
Subject: clustering of all Machine Learning in Medicine articles
Date: Sun, 2 Mar 2003 08:13:05 -0500
Hi, this URL may be of interest to ML list subscribers:
http://vivisimo.com/search?v:file=ML_in_Medicine
It's an automatic hierarchical clustering of all PubMed articles that
mention Machine Learning.
Cordially,
Raul Valdes-Perez
------------------------------
From: Sunita Sarawagi <[EMAIL PROTECTED]>
Subject: SIGKDD Explorations Volume 4, Issue 2 available online
Date: Wed, 12 Mar 2003 23:17:09 +0530
We are please to announce that the SIGKDD Explorations Volume 4, Issue
2 is available online at: http://www.acm.org/sigkdd/explorations/
Johannes Gherke served as Guest Editor for this issue and coordinated
a set of high-quality articles on the topic of Privacy and Security
issues in data mining. This issue also includes writeups from the
winning entries of last year's KDD Cup competition and reports of
other events from KDD 2002.
Table of Contents:
Contributed Articles on Privacy and Security
Data Mining, National Security, Privacy and Civil Liberties
B. Thuraisingham
The Inference Problem: A Survey
C. Farkas and S. Jajodia
Cryptographic Techniques for Privacy-Preserving Data Mining
B. Pinkas
Database Privacy
M. Olivier
Tools for Privacy Preserving Data Mining
C. Clifton, M. Kantarcioglu, J. Vaidya, X. Lin and M.Y. Zhu
Applying Data Mining to Intrusion Detection: The Quest for Automation,
Efficiency, and Credibility
W. Lee
Randomization in Privacy-Preserving Data Mining
A. Evfimievski
Contributed Articles
A Survey on Wavelet Applications in Data Mining
T. Li, Q. Li, S. Zhu, and M. Ogihara
A Perspective on Inductive Databases
L. De Raedt
The True Lift Model - A Novel Data Mining Approach to Response
Modeling in Database Marketing
V. S. Y. Lo
Reports from KDD-2002
Background and Overview for KDD Cup 2002 Task 1: Information
Extraction from Biomedical Articles
A. Yeh, L. Hirschman, A. Morgan
Rule-based Extraction of Experimental Evidence in the Biomedical
Domain - the KDD Cup (Task 1)
Y. Regev, M. Finkelstein-Landau, and R. Feldman
A Machine Learning Approach for the Curation of Biomedical Literature
- KDD Cup 2002 (Task 1)
S.S. Keerthi, C.J. Ong, K.B. Siah, D.B.L. Lim, W. Chu, M. Shi,
D. S. Edwin, R. Menon, L. Shen, J.Y.K. Lim, and H.T. Loh
Automatic Scientific Text Classification Using Local Patterns: KDD CUP
2002 (Task 1)
M. M. Ghanem, Y. Guo, H. Lodhi, and Y. Zhang
The Genomics of a Signaling Pathway: A KDD Cup Challenge Task
M. Craven
One Class SVM for Yeast Regulation Prediction
A. Kowalczyk and B. Raskutti
Predicting the Effects of Gene Deletion
D. S. Vogel and R. C. Axelrod
Combining Data and Text Mining Techniques for Yeast Gene Regulation
Prediction: A Case Study
M.-A. Krogel, M. Denecke, M. Landwehr, and T. Scheffer
Feature Engineering for a Gene Regulation Prediction Task
G. Forman
P-tree Classification of Yeast Gene Deletion Data
A. Perera, A. Denton, P. Kotala, W. Jockheck, W. V. Granda, and
W. Perrizo
Report on the SIGKDD-2002 Panel The Perfect Data Mining Tool:
Interactive or Automated
M. Ankerst
BIOKDD 2002: Recent Advances in Data Mining for Bioinformatics
M. J. Zaki, J. T. L. Wang, H. T. T. Toivonen
KDD-2002 Workshop Report Fractals and Self-similarity in Data Mining:
Issues and Approaches
J. Adibi and C. Faloutsos
MDM/KDD2002: Multimedia Data Mining between Promises and Problems
S. J. Simoff and C. Djeraba
Multi-Relational Data Mining: a Workshop Report
S. Dzeroski and L. De Raedt
WEBKDD 2002 - Web Mining for Usage Patterns & Profiles
B. M. Masand, M. Spiliopoulou, J. Srivastava, and O. R. Zaiane
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End of ML-LIST Digest Vol 15, No. 5
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