Machine Learning List
Sat, 01 Mar 2003 14:49:02 -0800
Machine Learning List: Vol. 15, No. 4
Saturday, March 1, 2003
Contents
Calls for Papers and Other Meeting Announcements
HLT/NAACL 2003 CFP: CoNLL-2003 7th Conf on Natural Language Learning
HLT/NAACL-2003 Workshop CFP: Building and Using Parallel Texts: Data
Call for Tutorial Proposals
Call for Special Session Proposals
Workshop: Learning from Imbalanced Data Sets
DATE CHANGE: Wrkshp on Advances in ML, Montreal, June 9-13, 2003
DMLL: ML journal Special issue on Data Mining Lessons Learned
Call for papers - ICMLC-2003
Extended Deadline: IJCAI-03 Workshop on ... Web Personalization
EXTENDED DEADLINE: HLT/NAACL-2003: Text Summarization ... (DUC-2003)
ICML Workshop on Machine Learning for Space
EXTENSION: IJCAI'03 Wrkshp Mixed-Initiative Intelligent Systems
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: Priscilla Rasmussen <[EMAIL PROTECTED]>
Subject: HLT/NAACL 2003 CFP: CoNLL-2003 7th Conf on Natural Language Learning
Date: Mon, 10 Feb 2003 11:44:19 EST
CALL FOR PAPERS
CoNLL-2003: Seventh Conference on Natural Language Learning
Organized at HLT-NAACL-02, Edmonton, Canada
May 31 - June 1 2003
http://cnts.uia.ac.be/conll2003/
CoNLL is an international forum for discussion and presentation of
research on natural language learning. We invite submission of papers
about natural language learning topics, including, but not limited to:
- Computational models of human language acquisition
- Computational models of the origins and evolution of language
- Machine learning methods applied to natural language processing
tasks (speech processing, phonology, morphology, syntax,
semantics, discourse processing, language engineering
applications)
- Symbolic learning methods (Rule Induction and Decision Tree
Learning, Lazy Learning, Inductive Logic Programming, Analytical
Learning, Transformation-based Error-driven Learning)
- Biologically-inspired methods (Neural Networks, Evolutionary
Computing)
- Statistical methods (Bayesian Learning, HMM, maximum entropy,
SNoW, Support Vector Machines)
- Reinforcement Learning
- Active learning, ensemble methods, meta-learning
- Computational Learning Theory analysis of language learning
- Empirical and theoretical comparisons of language learning methods
- Models of induction and analogy in Linguistics
See http://www.aclweb.org/signll and
http://ilk.uvt.nl/~signll/conll.html for more information about SIGNLL
and CoNLL.
SPECIAL THEME
As in previous years, in addition to submissions on the general topics
listed above, we encourage submissions on a special theme. This year's
special theme is:
Semi-supervised / unsupervised learning and sample selection
techniques for language learning (co-training, active learning,
EM, etc).
Supervised Machine Learning methods suffer from a "data annotation
bottleneck" which is especially harmful for language learning tasks
where a lot of training data is needed (e.g. parsing). Sample
selection techniques, and combination of supervised learning with
semi-supervised and unsupervised techniques may provide a solution to
this problem.
SHARED TASK
This year's workshop will also accept submissions for a shared task:
machine learning approaches to named entity recognition. Special
attention will be given to the use of multiple sources of knowledge,
like training data, lists of examples and unannotated data.
Interested groups will be supplied with the same training and testing
material (in several languages), and will all use the same evaluation
criteria, thus allowing comparison between various learning methods.
More information on the shared task will be available at:
http://cnts.uia.ac.be/conll2003/ner/
IMPORTANT DATES
Deadline for Paper Submission: March 16, 2003
Deadline for Shared Task Submission: March 16, 2003
Notification: March 24, 2003
Deadline camera-ready paper: April 10, 2003
Conference: May 31-June 1 2003
------------------------------
From: Priscilla Rasmussen <[EMAIL PROTECTED]>
To: [EMAIL PROTECTED]
Subject: HLT/NAACL-2003 Workshop CFP: Data Driven Machine Translation
Date: Mon, 10 Feb 2003 11:50:43 EST
C A L L F O R P A P E R S
Building and Using Parallel Texts:
Data Driven Machine Translation and Beyond
An HLT-NAACL 2003 Workshop
Edmonton, Alberta
May 31 or June 1, 2003
http://www.cs.unt.edu/~rada/wpt
The goal of this workshop is to provide a forum for researchers
working on problems related to the creation and use of parallel
text. Recent events have demonstrated once again the importance of
inter-language communication, and reinforce the need for advances in
machine translation (MT) and multi-lingual processing tools.
The workshop will be centered around the problem of building and using
parallel corpora, which are vital resources for efficiently deriving
multi-lingual text processing tools. In addition to regular papers,
the workshop also includes a shared task that will result in a
comparative evaluation of word alignment techniques.
While we invite submissions addressing any of the above topics, or
related issues, we particularly welcome work involving parallel
corpora addressing languages with scarce resources.
SHARED TASK:
All researchers who have a word alignment system available are invited
to participate in the shared task, individually or as part of a team.
Participants in the shared task will be provided with common sets of
training data, consisting of Romanian-English and French-English
parallel texts. Participants will be given approximately one month to
train their systems with this data, and then previously held out test
data will be released. Participants will run their alignment system on
this test data and submit their results, which will be evaluated using
a common set of metrics. See the workshop website for details
regarding the shared task.
IMPORTANT DATES:
Deadline for regular paper submissions: March 10
Deadline for results submissions: March 25 (shared task)
Deadline for short paper submissions: April 1 (shared task)
Notification of acceptance for regular papers: April 1
Deadline for camera-ready papers: April 10
------------------------------
From: Eugene Eberbach <[EMAIL PROTECTED]>
Subject: Call for Tutorial Proposals
Date: Mon, 10 Feb 2003 17:33:55 -0500
CEC2003 - Congress on Evolutionary Computation
Canberra, Australia, December 8-12, 2003
http://www.cs.adfa.edu.au/cec_2003/
The Program Committee of CEC2003 welcomes proposals for tutorials on
all aspects of evolutionary computation and its applications, or
closely related fields.
Tutorials should be a means for senior researchers to present an
overview of a field related to evolutionary computation. A tutorial
should not be a technical presentation focusing on ones own work only.
It should preferably handle a relatively large chunk of knowledge on a
specific area, typically at an introductory level. Comprehensive
references must also be provided.
IMPORTANT DATES
April 4, 2003: Deadline for tutorial proposals
May 2, 2003: Notification of tutorial acceptance
Sept. 15, 2003: Electronic version of tutorial notes due
(PostScript, PDF, Word or PowerPoint)
Dec. 8-12, 2003: CEC2003
SUBMISSION DETAILS
Proposals for tutorials should be one page in length and should
contain the following information:
1. Title
2. Name and full contact information of the proposer(s), together with
one paragraph explaining why she/he/they is/are the right person for
that topic.
3. A brief description (one or two paragraphs) of the intended contents.
4. The preferred length of their tutorial (2h, 3h, or 4h, knowing that
not all wishes will come true)
5. Any resource requirements, e.g. computers, equipment setup, 3D
projector, etc.
6. An optional label being either "novice" (e.g. Intro to GP) or
"advanced" (e.g. Recent advances in parallel GAs).
Proposals should be sent in plain ASCII (iso8859-1) TEXT format to
both the tutorial chairs
[EMAIL PROTECTED], [EMAIL PROTECTED]
no later than April 4. 2003.
------------------------------
From: Eugene Eberbach <[EMAIL PROTECTED]>
Subject: Call for Special Session Proposals
Date: Mon, 10 Feb 2003 17:37:12 -0500
CEC2003 - Congress on Evolutionary Computation
Canberra, Australia, December 8-12, 2003
http://www.cs.adfa.edu.au/cec_2003/
CEC'03 is now inviting special session proposals. All special sessions
are to be organized around a specific topic in order to encourage
in-depth discussions. Special sessions will be an integral part of the
conference. All accepted papers in the special sessions will be
included in the published conference proceedings. All special session
papers will be reviewed, and the review process will be coordinated
and supervised by the special session organizer(s).
Each proposal should contain at least the following information:
(1) Title of the session;
(2) Name of the organizer(s) and their detailed contact addresses;
(3) One or two paragraphs describing the theme and topics covered by the
session.
The accepted special sessions will be posted and updated regularly on
the conference homepage (http://www.cs.adfa.edu.au/cec_2003.html). To
propose a special session, email your proposal to Dr KC Tan
([EMAIL PROTECTED]), CEC'03 Special Sessions Co-Chair.
------------------------------
From: Nathalie Japkowicz <[EMAIL PROTECTED]>
Subject: Workshop: Learning from Imbalanced Data Sets
Date: Tue, 11 Feb 2003 12:30:17 -0500 (EST)
CALL FOR PAPERS
ICML-KDD'2003 Workshop:
Learning from Imbalanced Data Sets II
Thursday, August 21, 2003
Washington, DC
WORKSHOP PAGE:
http://www.site.uottawa.ca/~nat/Workshop2003/workshop2003.html
OVERVIEW:
Recent years brought increased interest in applying machine learning
techniques to difficult "real-world" problems, many of which are
characterized by imbalanced learning data, where at least one class is
under-represented relative to others. Examples include (but are not
limited to): fraud/intrusion detection, risk management, medical
diagnosis/monitoring, bioinformatics, text categorization and
personalization of information. The problem of imbalanced data is
often associated with asymmetric costs of misclassifying elements of
different classes. Additionally the distribution of the test data may
differ from that of the learning sample and the true misclassification
costs may be unknown at learning time.
The AAAI-2000 Workshop on "Learning from Imbalanced Data Sets"
provided the first venue where this important problem was explicitly
addressed and has been received with much interest. The related
ICML-2000 Workshop on "Cost-Sensitive Learning" provided another venue
for addressing the problem of asymmetric costs of different classes
and features. Although much awareness of the issues related to data
imbalance has been raised, many of the key problems still remain open
and are in fact encountered more often, especially when applied to
massive datasets. We believe that it would be of value to the machine
learning community to not only examine the progress achieved in this
area over the last three years but also discuss the current school of
thought on research in learning from imbalanced datasets. Based on our
understanding of class imbalance problem, the following topics of
discussion are proposed (but not limited to):
* sampling (under-, over-, progressive, active)
* post-processing of learned models
* accounting for class imbalance via inductive bias
* one-sided learning
* handling uncertainty of target distribution and misclassification costs
* handling varying amounts (class dependent) of label noise
SUBMISSIONS:
Authors are invited to submit papers on the topics outlined above or
on other related issues. Submissions should not exceed 8 pages, and
should be in line with the ICML style sheet. Electronic submissions,
in PDF format, are prefered and should be sent to:
Nitesh Chawla at [EMAIL PROTECTED]
TIMETABLE:
Submission deadline: May 1, 2003
Notification date: May 25, 2003
Final date for camera-ready copies to organizers: June 8, 2003
------------------------------
From: Balazs Kegl <[EMAIL PROTECTED]>
Subject: DATE CHANGE: Wrkshp on Advances in ML, Montreal, June 9-13, 2003
Date: Tue, 11 Feb 2003 14:16:56 -0500
Due to a date conflict with a major conference, we have had to
reschedule the Workshop on Advances in Machine Learning from June 2-6
to June 9-13. We apologize for the inconvenience it may cause. The
paper submission deadline remains March 31.
Call for papers
Workshop on Advances in Machine Learning
Montreal, Canada, June 9-13, 2003
URL: www.iro.umontreal.ca/~lisa/workshop2003.html
IMPORTANT DATES:
March 31, Paper submission deadline
April 15, Notification of paper acceptance/rejection.
------------------------------
From: Hiroshi Motoda <[EMAIL PROTECTED]>
Subject: DMLL: ML journal Special issue on Data Mining Lessons Learned
Date: Tue, 18 Feb 2003 15:44:22 +0900
Machine Learning Journal:
Special Issue on Data Mining Lessons Learned
http://www.hpl.hp.com/personal/Tom_Fawcett/DMLL-MLJ-CFP.html
Guest editors:
Nada Lavrac, Hiroshi Motoda and Tom Fawcett
Submission deadline: Monday, 7 April, 2003.
CALL FOR PAPERS
Data mining is concerned with finding interesting or valuable patterns
in data. Many techniques have emerged for analyzing and visualizing
large volumes of data, and what we see in the technical literature are
mostly success stories of these techniques. We rarely hear of steps
leading to success, failed attempts, or critical representation
choices made; and rarely do papers include expert evaluations of
achieved results. Insightful analyses of successful and unsuccessful
applications are crucial for increasing our understanding of machine
learning techniques and their limitations.
Challenge problems (such as the KDD Cup, COIL and PTE challenges) have
become popular in recent years and have attracted numerous
participants. These challenge problems usually involve a single
difficult problem domain, and participants are evaluated by how well
their entries satisfy a domain expert. The results of such challenges
can be a useful source of feedback to the research community.
At ICML-2002 a workshop on Data Mining Lessons Learned was held and
(http://www.hpl.hp.com/personal/Tom_Fawcett/DMLL-workshop.html) and
was well attended. This special issue of the Machine Learning journal
follows the main goals of that workshop, which are to gather
experience from successful and unsuccessful data mining endeavors, and
to extract the lessons learned from them.
SUBMISSION INSTRUCTIONS
Manuscripts for submission should be prepared according to the
instructions at http://www.cs.ualberta.ca/~holte/mlj/
In preparing submissions, authors should follow the standard
instructions for the Machine Learning journal at
http://www.cs.ualberta.ca/~holte/mlj/initialsubmission.pdf
Submissions should be sent via email to Hiroshi Motoda
([EMAIL PROTECTED]), as well as to Kluwer Academic
Publishers ([EMAIL PROTECTED]). In the email please state very clearly that
the submission is for the special issue on Data Mining Lessons
Learned.
------------------------------
From: "Jacobus van Zyl" <[EMAIL PROTECTED]>
Subject: Call for papers - ICMLC-2003
Date: Wed, 19 Feb 2003 12:34:37 +0100
Call for Papers
International Conference on Machine Learning and Cybernetics 2003
Sponsored by
Machine Learning Centre
Hebei University, Baoding, Hebei, China
and
IEEE Systems, Man and Cybernetics Technical Committee on Cybernetics
24-27 August 2003
Xi-an, China
The second International Conference on Machine Learning and
Cybernetics (ICMLC-2003) sponsored by the Machine Learning Centre of
the Hebei University (www.hbu.edu.cn) and the IEEE Systems, Man and
Cybernetics Technical Committee on Cybernetics
(www.isye.gatech.edu/ieee-smc), will be held in Xi-an, China on 24-27
August 2003. We are living in a world which is rapidly evolving from
an information-based to a knowledge-based society. In this new
environment, we must be able to effectively turn the data we have into
knowledge for our survival and advancement. Machine learning plays an
important role in helping us generate new knowledge from data, whereas
cybernetics provides a framework for the applications and
implementations. This conference will bring together researchers, as
well as people and organizations interested in machine learning and
cybernetics applications, to exchange ideas and report progress in
this important and exciting area of research and development.
TOPICS FOR SUBMISSION:
We invite original papers in machine learning an cybernetics
including, but not limited to the following topics:
* Adaptive Systems * Information Retrieval
* Artificial Neural Networks * Intelligent Agents
* Approximate Reasoning * Intelligent DSS
* Case-Based Reasoning * Intelligent Control Systems
* Data-Mining * Knowledge Based Systems
* Evolutionary Computation * Knowledge Representation
* Feature Selection * Pattern Recognition
* Fuzzy Control * Speech Recognition
* Fuzzy Systems and Theory * Support Vector Machines
* Hybrid Systems * Wavelet & Multi-Resolution
* Inductive Learning * Web-Mining
Machine Learning Applications in:
* Bio-Informatics
* Construction Project Management
* Financial Engineering
* Geo-Informatics
* Intelligent Transportation Systems
* Logistics
* Medical Informatics
* Natural Language Processing
* Network Intrusion Detection
* Power Supply
IMPORTANT DATES:
Submissions due: 15 April 2003
Notification of acceptance: 15 June 2003
Camera-ready copies of accepted papers due: 15 July 2003
Conference: 24-27 August 2003
Conference Website (under construction):
http://www.icmlc2003.hbu.edu.cn
------------------------------
From: "Sarabjot Singh Anand" <[EMAIL PROTECTED]>
Subject: Extended Deadline: IJCAI-03 Workshop on ... Web Personalization
Date: Sun, 23 Feb 2003 22:52:42 -0000
The IJCAI 2003 Workshop on Intelligent Techniques for Web
Personalization (ITWP '03) will be held on Monday, August 11, 2003 in
Acapulco, Mexico
Since the publishing of the first call for papers, we have recieved
confirmation from Elsevier of the acceptance of our proposal for a
post-workshop book on Intelligent Techniques for Web Personalisation
as part of the Lecture Notes in Artificial Intelligence
(State-of-the-Art Survey) series. The best papers from the workshop
will be invited to submit chapters for publication in the book. In
view of this development we have decided to Extend the Deadline for
papers.
Important Dates and Deadlines
Abstract Submission: March 14, 2003
Full Paper Submission: March 21, 2003
Notification of Acceptance: April 20, 2003
Camera Ready Papers Due: May 23, 2003
For additional information on the workshop please visit the workshop
web site at: http://maya.cs.depaul.edu/~mobasher/itwp03/ which will
provide additional details including the Topics of interest, paper
format requirements and the programme committee. Also please feel free
to e-mail the workshop co-chairs for any questions that remain
unanswered.
------------------------------
From: Priscilla Rasmussen <[EMAIL PROTECTED]>
Subject: EXTENDED DEADLINE: HLT/NAACL-2003: Text Summarization ... (DUC-2003)
Date: Wed, 26 Feb 2003 17:14:26 EST
!!SUBMISSION DEADLINE EXTENDED TO MARCH 7, 2003!!
HLT-NAACL Text
Summarization Workshop
and
Document Understanding Conference (DUC 2003)
May 31 and June 1, 2003
Edmonton, AB, Canada
http://www.umich.edu/cl/hlt-naacl-duc03/
Given that the ACL'03 deadline is tomorrow and that most other
HLT-NAACL'03 workshop deadlines are not until early March, the
submission deadline for the HLT-NAACL'03 has been extended by a week
to March 7.
REVISED SCHEDULE
- March 7, 2003 - submissions due
- March 28, 2003 - authors notified
- April 10, 2003 - camera-ready papers due
Please visit the workshop site for submissions details and additional
information.
------------------------------
From: Kiri Wagstaff <[EMAIL PROTECTED]>
Subject: ICML Workshop on Machine Learning for Space
Date: Thu, 27 Feb 2003 09:41:48 -0500 (EST)
Call for Papers and Participation: ICML-2003 Workshop
Machine Learning Technologies for Autonomous Space Applications
Thursday, August 21, 2003, Washington, D.C.
http://www.lunabots.com/icml2003/
Submission deadline: May 1, 2003
The ICML 2003 workshop on Machine Learning Technologies for Autonomous
Space Applications invites contributions from researchers and
practitioners in machine learning, space science, and mission
planning. This workshop aims to bring together those interested in
developing novel machine learning algorithms for autonomous spacecraft
with those concerned with misson safety, performance, and engineering
constraints to bridge the "applicability divide". Despite progress in
developing applicable ML techniques, adoption and integration into
fielded remote space missions remains a challenge. The workshop will
provide a context for mission engineers and scientists to present
their "wish lists" and real-world constraints to machine learning
researchers and for ML scientists to present pertinent, cutting-edge
technologies. The ultimate goal is to foster research and development
leading to the application of machine learning methods on real, flown
spacecraft.
We convene this workshop as a forum where we can address critical
questions such as:
* How can we design algorithms that can train for a long time under
controlled situations, but must work almost perfectly in a remote,
autonomous setting?
* How can ML techniques be tested so as to convince someone outside
the field that they are reliable, robust, and effective for real
space systems? What are the best analogue problems and situations,
here on Earth, for the development and study of applicable ML
techniques?
* Are there specific, possibly novel, metrics and methodologies for
evaluation that would be most appropriate for these problems?
* What ML algorithms drawn from other domains (e.g., tasks with a high
cost of failure) are applicable to the problems faced by fielded
space missions?
* Can we provide formal performance guarantees for ML algorithms in
the constrained and sometimes hostile environments in which remote
space systems will exist?
* How can we strengthen connections between ML researchers and the
people making operational decisions for space missions?
For a full description of the workshop focus and goals, visit the
website at http://www.lunabots.com/icml2003/ .
Important Dates:
May 1, 2003: Technical submissions due
May 25, 2003: Notification of acceptance
June 6, 2003: Camera ready copies due
August 1, 2003: Attendance-only submissions due
------------------------------
From: "David W. Aha" <[EMAIL PROTECTED]>
Subject: EXTENSION: IJCAI'03 Wrkshp Mixed-Initiative Intelligent Systems
Date: Thu, 27 Feb 2003 10:31:58 -0500
This is to announce a revised submission deadline for this workshop
IJCAI'03 Workshop on Mixed-Initiative Intelligent Systems
Acapulco, Mexico, August 9th, 2003
Submission deadline: March 16th, 2003
http://lalab.gmu.edu/MIIS/default.htm
------------------------------
End of ML-LIST Digest Vol 15, No. 4
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