Stipends available for  MSc Intelligent Systems
----------------------------------

We are pleased to announce that for eligible students we have obtained
funding  to offer a bursary for our new MSc Intelligent Systems
worth up to 6000 pounds or about 14.000 EURO as fee waiver and
stipend for eligible EU students. Please forward to  students who
may be interested

The School of Computing and Technology, University of Sunderland
is delighted to announce the launch of its new MSc Intelligent Systems
programme for 24th  February. Building on the School's leading edge
research in intelligent systems this masters programme will be
funded via the ESF scheme  (see below).

Intelligent Systems is an exciting field of study for science and
industry  since the currently existing computing systems have
often not yet  reached the various aspects of  human performance.
"Intelligent Systems" is a term to describe software systems and
methods, which simulate aspects of intelligent behaviour. The intention
is  to learn from nature and human performance in order to build more
powerful computing systems. The aim is to learn from cognitive science,
neuroscience, biology, engineering, and linguistics for building more
powerful computational system architectures. In this programme a
wide variety of novel and exciting techniques will be taught including
neural networks, intelligent robotics, machine learning, natural language
processing,  vision, evolutionary genetic computing, data mining,
information retrieval,  Bayesian computing, knowledge-based systems,
fuzzy methods, and  hybrid intelligent architectures.

Programme Structure
--------------
The following lectures/modules are available:

Neural Networks
Intelligent Systems Architectures
Learning Agents
Evolutionary Computation
Cognitive Neural Science
Knowledge Based Systems and Data Mining
Bayesian Computation
Vision and Intelligent Robots
Natural Language Processing
Dynamics of Adaptive Systems
Intelligent Systems Programming


Funding up to 6000 pounds (about 14.000Euro) for eligible students
------------------------------

The Bursary Scheme applies to this Masters programme commencing
February 2003 and we have obtained funding through the European
Social Fund (ESF). ESF  support enables the University to waive the
normal tuition fee and provide  a bursary of £ 75 per week for 45 weeks
for eligible EU students,  together up to 6000 pounds or 14000 Euro.

For further information in the first instance please see:
http://osiris.sund.ac.uk/webedit/allweb/courses/progmode.php?prog=G550A&mode=FT&\
mode2=&dmode=C

For information on applications and start dates contact:
         gillian.potts@...  Tel: 0191 515 2758
For academic information about the programme contact:
         alfredo.moscardini@...



***************************************
Professor Stefan Wermter
Chair for Intelligent Systems
Informatics Centre
School of Computing and Technology
University of Sunderland
St Peters Way
Sunderland SR6 0DD
United Kingdom

phone: +44 191 515 3279
fax:   +44 191 515 3553
email: stefan.wermter@...
http://www.his.sunderland.ac.uk/~cs0stw/
http://www.his.sunderland.ac.uk/

----------------------------------------------------------------------
         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/ .

----------------------------------------------------------------------
Format
----------------------------------------------------------------------

This will be a one-day workshop.  The day will open with a keynote
presentation by Dr. Steve Chien of JPL, a renowned expert in automated
planning and scheduling for space exploration.  In addition, the
program will feature a mix of technical presentations by machine
learning and space mission scientists, ample discussion sessions, and
a small-group brainstorming exercise built around exemplar practical
scenarios.

----------------------------------------------------------------------
Paper Submissions
----------------------------------------------------------------------

We welcome contributions of innovative, controversial, yet well
reasoned ideas.  Papers, 3-5 pages in length, may be submitted on one
of three topics: technical challenges/solutions, social
challenges/solutions, or opportunities for the use of ML in space
missions.  In addition, interested participants who do not wish to
submit a technical paper may submit a one-page statement of interests
and potential contributions to the workshop.

For more details, including paper format and submission address, see:
   http://www.lunabots.com/icml2003/CFP.html#sub

----------------------------------------------------------------------
Important Dates
----------------------------------------------------------------------

May 1, 2003:    Technical submissions due
May 25, 2003:   Notification of acceptance
June 6, 2003:   Camera ready copies of both bios and technical submissions
August 1, 2003: Attendance-only submissions due
   Note that biographies submitted in this category after the June 6
   camera-ready date may not appear in the proceedings, though we will
   attempt to make them available on the workshop web site.

----------------------------------------------------------------------
Program Committee
----------------------------------------------------------------------

Kiri Wagstaff (JHU/APL) - Co-chair
Amy McGovern (University of Massachusetts Amherst) - Co-chair
Terran Lane (University of New Mexico) - Co-chair
Jim Bell (Cornell University)
Steve Chien (NASA/JPL)
Dennis DeCoste (NASA/JPL)
Manfred Huber (University of Texas at Arlington)
Ted Roush (NASA/Ames)
Donna Shirley (University of Oklahoma)
Tim Stough (NASA/JPL)

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

Dear all,

I am wondering if someone is aware of studies that compare different
classification system inducers on synthetic data with particular
features. Such features may be: specific types of noise, data exhibiting
the Simpson paradox, non-linearly separable class distributions etc.
(any further ideas?)

Any pointers would be very much appreciated. Many thanks in advance!

--
All the best
Chris

Dear all,

I am wondering if someone is aware of studies that compare different
classification system inducers on synthetic data with particular
features. Features might be: specific types of noise, data exhibiting
the Simpson paradox, non-linearly separable class distributions etc.
(any further ideas?)

Any pointers would be very much appreciated. Many thanks in advance!

--
All the best
Chris

Dear Colleagues,

Please be informed that the deadline of the SEKE 2003 Workshop on Data
Mining for Software Engineering and Knowledge Engineering has been extended
to 10 March 2003.

The CFPs is attached.

Best regards

Honghua Dai

[Non-text portions of this message have been removed]

Hi everybody,

  We are interested in investigating methods of distinguishing causal and
acausal relations based on time (rather than the more traditional method
of conditional idependence).

  For this reason I am looking for a rather peculiar kind of data: I am
looking for causal relations in temporal data. By temporal I mean the data
should have produced at regular intervals (every second, every day, etc.).
For a causal relation to exist, the data should come from a single
source, and should have the value of at least a few related variables. (A
time-series dataset is not very useful because a single variable can
hardly be used for causality purposesd).

  The above two rquierements mean that "census-type" data whihc abound on
the Internet are not suitable. First because there is no temporal order
among each field, and second because they come from different "systems"
(peopel, things, etc).

  I wonder if anybody on this list knows of such temporal data, or of any
application program that can process such data.

  I would be grateful for any help.

  Kamran Karimi
karimi@...
http://www.cs.uregina.ca/~karimi

----------------------------------------------------------------------
      Second 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/ .  We also encourage you
to join the mailing list for announcements and discussion.  Send an
email to  majordomo@... with "subscribe icml2003-mlspace" in
the body.

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

Chairs: Kiri Wagstaff (JHU/APL), Amy McGovern (UMass Amherst), and
Terran Lane (UNM)

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

***NEW DEADLINE APRIL 27TH 2003***

                    ***REGISTRATION FEE REDUCED***


Due to a last minute success in fundraising for the school we were able
to reduce the registration fee to EUR 600,-.

We now also have fellowships for covering the tuition fee and travel
expenses for students who need financial help for attending the course.


===========================================================================


ADVANCED COURSE IN COMPUTATIONAL NEUROSCIENCE
(A FENS/IBRO NEUROSCIENCE SCHOOL)

August 11th - September 5th, 2003

MUNICIPALITY OF OBIDOS, PORTUGAL

DIRECTORS: Ad Aertsen (University of Freiburg, Germany)
            Alain Destexhe (CNRS, Gif-sur-Yvette, France)
            Klaus Obermayer (Technical University of Berlin, Germany)
            Eilon Vaadia (Hebrew University, Jerusalem, Israel)

The Advanced Course in Computational Neuroscience introduces students
to the panoply of problems and methods of computational neuroscience,
simultaneously addressing several levels of neural organisation, from
subcellular processes to operations of the entire brain.

The course consists of two complementary parts. A distinguished
international faculty gives morning lectures on topics in experimental and
computational neuroscience. The rest of the day is devoted to practical
training, including learning how to use simulation software and how to
implement a model of the system the student wishes to study on individual
UNIX workstations.

The first week of the course introduces students to essential
neurobiological concepts and to the most important techniques in modelling
single cells, networks and neural systems. Students learn how to apply
software packages like GENESIS, MATLAB, NEURON, XPP, etc. to the solution
of their problems. During the following three weeks the lectures will cover
specific brain functions. Each week topics ranging from modelling single
cells and subcellular processes through the simulation of simple circuits,
large neuronal networks and system level models of the brain will be
covered. The course ends with a presentation of the students' projects.

The Advanced Course in Computational Neuroscience is designed for advanced
graduate students and postdoctoral fellows in a variety of disciplines,
including neuroscience, physics, electrical engineering, computer science
and psychology. Students are expected to have a basic background in
neurobiology as well as some computer experience. Students of any
nationality can apply.

A maximum total of 30 students will be accepted and we specifically
encourage applications from researchers who work in less-favoured regions
and women. There will be a fee of EUR 600,- per student covering costs
for lodging, meals and other course expenses, but - due to additional
funding - we expect to provide tuition fee waivers and travel stipends
for students who need financial help for attending the course. Students
from unfavored countries are strongly encouraged to apply.

More information and application forms can be obtained from:

           http://www.neuroinf.org/courses/EUCOURSE/EU03/

Please apply electronically using a web browser.

Contact address:

        - mail:   Klaus Obermayer, FR2-1, Fakultaet IV, Technical University
		  of Berlin, Franklinstrasse 28/29, 10587 Berlin, Germany
                  phone: +49-(0)30-314-73442
                  fax:   +49-(0)30-314-73121
        - e-mail: obidos@...

APPLICATION DEADLINE:  April 27th, 2003

Applicants will be notified of the results of the selection procedures by
May 23rd, 2003.


CONFIRMED FACULTY:

Larry Abbott, Brandeis University, USA
Moshe Abeles, Hebrew University, Israel
Ad Aertsen, University of Freiburg, Germany
Amos Arieli, Weizmann Institute, Israel
Thierry Bal, CNRS, France
Dave Beeman, University of Colorado Boulder, USA
Diego Contreras, University of Pennsylvania, USA
Peter Dayan, University College London, UK
Erik de Schutter, University of Antwerp, Belgium
Alain Destexhe, CNRS, France
Marcus Diessmann, University of Freiburg, Germany
Andreas Engel, University of Hamburg, Germany
Karl Friston, University College London, UK
Michael Hines, Yale University, USA
Israel Nelken, Hebrew University, Israel
Miguel Nicolelis, Duke University, USA
Klaus Obermayer, TU Berlin, Germany
Tim Pearce, University of Leicester, UK
John Rinzel, New York University, USA
Arnd Roth, Max Planck Inst. Heidelberg, Germany
Michael Rudolph, CNRS, France
Lars Schwabe, TU Berlin, Germany
Idan Segev, Hebrew University, Israel
Volker Steuber, University of Antwerp, Belgium
Alex Thomson, University College London, UK
Charlie Wilson, University of Texas San Antonio, USA
Daniel Wolpert, University College London, UK
Eilon Vaadia, Hebrew University, Israel
Carl van Vreeswijk, CNRS, France
Paul Verschure, Inst. Neuroinformatics, Switzerland

Dear all,

I am a student at the University of Patras, Greece. I am working on
machine-learning in natural language processing and I would be interested in
work regarding imbalanced data sets (where some classes to be classified are
rare). I would be thankful for any paper, report, software that deals with this
problem. Thank you very much in advance.

Best,

Katia Kermanidis
Wire Communications Laboratory
University of Patras, Greece
kerman@...


[Non-text portions of this message have been removed]

Katia Kermanidis wrote:

> Dear all,
>
> I am a student at the University of Patras, Greece. I am working on
> machine-learning in natural language processing and I would be interested
> in work regarding imbalanced data sets (where some classes to be classified
> are rare). I would be thankful for any paper, report, software that deals
> with this problem. Thank you very much in advance.

This might be a good starting point:
http://www.site.uottawa.ca/~nat/Workshop2003/workshop2003.html

					 Juffi
--
Johannes Fuernkranz
Austrian Research Inst. for Artificial Intelligence

Your help with circulating this announcement locally is much appreciated.
Apologies for multiple postings.

+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

                                    ISIPTA '03
3rd International Symposium on Imprecise Probabilities and Their Applications
                              Call for Participation

                                July 14-17, 2003
                              Lugano, Switzerland
                         http://www.sipta.org/~isipta03

+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

The ISIPTA meetings are one of the primary international forums to present
and discuss
new results on the theory and applications of imprecise probabilities.
Imprecise
probability has a wide scope, being a generic term for the many mathematical or
statistical models which measure chance or uncertainty without sharp numerical
probabilities. These models include belief functions, Choquet capacities,
comparative
probability orderings, convex sets of probability measures, fuzzy measures,
interval-valued probabilities, possibility measures, plausibility measures,
and upper
and lower expectations or previsions. Imprecise probability models are
needed in
inference problems where the relevant information is scarce, vague or
conflicting,
and in decision problems where preferences may also be incomplete.

Location
--------
ISIPTA '03 will be held at the University of Lugano, Switzerland, in the days
14-17 July 2003.
(http://www.sipta.org/~isipta03/venue.html)

Invited tutorials (14 July 2003)
--------------------------------
The tutorials will provide a gentle introduction to a wide range of
important subject
matters in imprecise probability, from foundational questions to models
with potential
for great impact on the application side.

1. Prof. Gert de Cooman, Ghent University, Belgium: A gentle introduction
to imprecise
     probability models and their behavioral interpretation.
2. Dr. Jean-Marc Bernard, Universitè Paris 5 & CNRS, France: Imprecise
Dirichlet model
     for multinomial data.
3. Prof. Charles F. Manski, Northwestern University, USA: Partial
identification of
     probability distributions.
4. Prof. Fabio G. Cozman, University of Sao Paulo, Brazil: Graphical models and
     imprecise probabilities.
5. Prof. Sujoy Mukerji, Oxford University, UK: Imprecise probabilities and
ambiguity
     aversion in economic modeling.
(http://www.sipta.org/~isipta03/tutorials.html)

Invited talks and contributions
-------------------------------
- Prof. Terrence L. Fine, Cornell University, USA (banquet speaker):
Theories of
    probability: some questions about foundations.
- Prof. Irving J. Good, Virginia Tech., USA: title will be available soon.
- Prof. Patrick Suppes, Stanford University, USA: Application of
nonmonotonic upper
    probabilities to quantum entanglement.
(http://www.sipta.org/~isipta03/invited.html)

The papers
----------
The 44 papers accepted for publication in the ISIPTA '03 proceedings have
gone through
a careful reviewing and selection process to the extent of doing
proceedings meeting
the highest standards.
(http://www.sipta.org/~isipta03/accepted.html).

Registration
------------
- Early registration by 31 May 2003: 600 (300) CHF for regular (student)
registration.
- Late registration by 30 June 2003: 700 (400) CHF for regular (student)
registration.
(1 CHF ~ 0.763 $.)
The registration fee includes the five tutorials on July the 14th, the
technical
sessions, the invited lectures, coffee breaks, lunches, evening tour, symposium
banquet, and a copy of the proceedings.
(http://www.sipta.org/~isipta03/register.html)

Program board
-------------
Jean-Marc Bernard (Université Paris 5, France)
Teddy Seidenfeld (Carnegie Mellon University, USA)
Marco Zaffalon (IDSIA, Switzerland)

Questions
---------
If you have any questions about the symposium, please contact the
Organising Committee,
at the following address:

Marco Zaffalon
IDSIA
Galleria 2
CH-6928 Manno
Switzerland

phone  +41 91 610 8665
fax    +41 91 610 8661
e-mail zaffalon@...

---------------------------------------------------------------------
          CART Data Mining'04: First International CART(R) Conferences
                 Focusing on the Data Mining technology of
           Leo Breiman, Jerome Friedman, Richard Olshen, Charles Stone
                 (CART, MARS(R), TreeNet(tm), PRIM(tm)...)

                        First Call For submissions
  ---------------------------------------------------------------------

               US Venue:  San Francisco, March 23-25, 2004
               EU Venue:  Madrid,        May   25-26, 2004

 	       Conference home page: http://www.cartdatamining.com

           ----------------------------------------------------------
           ---                                                    ---
           ---               CALL FOR SUBMISSIONS                 ---
           ---        Submission deadline: October 27, 2003       ---
           ---                                                    ---
           ----------------------------------------------------------

  Keynote Speakers:

 	 Leo Breiman,     University of California, Berkeley
 	 Jerome Friedman, Stanford University
 	 Richard Olshen,  Stanford University
 	 Charles Stone,   University of California, Berkeley

  Conference Sponsor:         Salford Systems

  The conferences are intended to serve several functions:

 	 o A festschrift and opportunity to honor the four
          authors of CART and meet with them in person. Each
          is planning to offer a keynote paper.

 	 o A venue to exchange ideas and experiences focused
          on the practice of data mining.

 	 o A networking opportunity leading to the creation of
 	 local user  groups and the establishment of a user
 	 newsletter.

 	 o A place to learn about extensions to CART related
 	 technology and anticipated future developments

 	 o An opportunity to obtain both basic and advanced training
 	 offered by practical and theoretical experts

  The conference series will provide an opportunity for data mining
  professionals to exchange ideas on the art and practice of the real
  world analysis of complex data.  Contributed papers covering any
  application of CART, MARS, PRIM, and TreeNet are encouraged,
  including innovative and unusual applications.

  Breiman's Random Forests will be the subject of an introductory
  tutorial.  A workshop devoted solely to RF will be scheduled separately.

          ----------------------------------------------------------
 			 Topics of Interest
          ----------------------------------------------------------

  We welcome applied data analysis papers from any industry or field of
  study.
  Illustrative industry sessions under consideration and requesting papers
  include

 	 Financial Services
 		 Targeted marketing, customer Acquisition
 		 Fraud Detection
 		 CRM: Customer Retention
 		 Risk management and score card development
 		 Loss management in insurance
 	 Financial Markets Modeling
 		 Stock Selection and Portfolio Management
 		 Business Cycle Forecasting
 	 Telecommunications
 		 Churn modeling
 		 Collections management
 		 Fraud detection
 	 Bioinformatics, Healthcare and Medicine
 		 DNA Microarray Data Analysis
 		 Proteomics
 		 Drug Discovery
 	 Web Mining and Text Mining
 		 User profiling
 		 Recommendation Systems
 		 Learning from Designed Experiments
                  eCommerce
 	 Engineering, Manufacturing, and Quality Control
 		 Semiconductor quality control
 	 Public Sector, Defense, Security

  Papers may have a methological focus and cover any key area of
  data mining such data quality assessment, missing value
  imputation, feature selection, model selection, ensemble methods,
  but should be rooted in a substantive industrial data mining
  context and report on real world data.

  Conference Participation

  If you have an interest in attending or presenting at this conference
  please let us know via email at info@.... The conference
  web site will contain a form for indicating the topic of a presentation
  you are considering presenting.

  Submission and Format of Papers

  Presentations may be in the form of technical papers or power point
  slide shows and are expected to last about 45 minutes. Technical papers
  should not exceed 6,000 words (approximately 20 A4 pages) and power
  point presentations should not exceed 40 slides.  If submitting
  powerpoint please include additional detailed discussion notes.

  We welcome submissions for either venue and expect that only a few
  papers will be presented at both locations.


  -----------------------------------------------------------------------
  IMPORTANT DATES
  -----------------------------------------------------------------------

  October 27,   2003    Submission deadline for contributed papers

  December 22,  2003    Notification of paper/presentation acceptance

  January  19,  2004   Camera-ready presentations due

  March 23-24,  2004    main conference San Francisco
  May   25-26   2004    Madrid conference
  -----------------------------------------------------------------------

Dear Colleagues,

I would like to ask you to send me references to papers that deal
with the problem of reliable classification.

Thank you very much in advance

Best regards

Evgueni Smirnov

I am attaching a paper that will be presented at the IJCNN03 next month. You
will have to evaluate its  reliability ... but I believe it is an interesting
application of un-supervised classification by ANN.

Sincerely,

Zvi Boger

OPTIMAL - Industrial Neural Systems
Be'er Sheva, Israel
  Rockville, MD, USA
>
> From: smirnov@...
> Date: 2003/06/19 ä PM 01:31:49 GMT+03:00
> To: machine-learning@yahoogroups.com
> Subject: [ML] reliable classification
>
> Dear Colleagues,
>
> I would like to ask you to send me references to papers that deal
> with the problem of reliable classification.
>
> Thank you very much in advance
>
> Best regards
>
> Evgueni Smirnov
>
>
> To UNSUBSCRIBE, send an empty message to
> machine-learning-unsubscribe@egroups.com
> To SUBSCRIBE, send an empty message to
> machine-learning-subscribe@egroups.com
> Archives: http://www.egroups.com/messages/machine-learning
>
>
> Your use of Yahoo! Groups is subject to http://docs.yahoo.com/info/terms/
>
>
>

I am attaching a paper that will be presented at the IJCNN03 next month. You
will have to evaluate its  reliability ... but I believe it is an interesting
application of un-supervised classification by ANN.

Sincerely,

Zvi Boger

OPTIMAL - Industrial Neural Systems
Be'er Sheva, Israel
  Rockville, MD, USA
>
> From: smirnov@...
> Date: 2003/06/19 ä PM 01:31:49 GMT+03:00
> To: machine-learning@yahoogroups.com
> Subject: [ML] reliable classification
>
> Dear Colleagues,
>
> I would like to ask you to send me references to papers that deal
> with the problem of reliable classification.
>
> Thank you very much in advance
>
> Best regards
>
> Evgueni Smirnov
>
>
> To UNSUBSCRIBE, send an empty message to
> machine-learning-unsubscribe@egroups.com
> To SUBSCRIBE, send an empty message to
> machine-learning-subscribe@egroups.com
> Archives: http://www.egroups.com/messages/machine-learning
>
>
> Your use of Yahoo! Groups is subject to http://docs.yahoo.com/info/terms/
>
>
>


[Non-text portions of this message have been removed]

Hi all,



Does anyone know any discussion group or mailing list specialized in
Bayesian Networks?



Thanks



Loukas Tsironis

Technical University of Crete



[Non-text portions of this message have been removed]

Stipends available for  MSc Intelligent Systems
----------------------------------

We are pleased to announce that for eligible EU students we have obtained
funding  to offer a bursary for our new MSc Intelligent Systems
worth up to 9.000 EURO as fee waiver and stipend.
***Please forward to  students who may be interested.***

The School of Computing and Technology, University of Sunderland
is delighted to announce the launch of its new MSc Intelligent Systems
programme for October 2003. Building on the School's leading edge
research in intelligent systems this masters programme will be
funded via the ESF scheme  (see below).

Intelligent Systems is an exciting field of study for science and
industry  since the currently existing computing systems have
often not yet  reached the various aspects of  human performance.
"Intelligent Systems" is a term to describe software systems and
methods, which simulate aspects of intelligent behaviour. The intention
is  to learn from nature and human performance in order to build more
powerful computing systems. The aim is to learn from cognitive science,
neuroscience, biology, engineering, and linguistics for building more
powerful computational system architectures. In this programme a
wide variety of novel and exciting techniques will be taught including
neural networks, intelligent robotics, machine learning, natural language
processing,  vision, evolutionary genetic computing, data mining,
information retrieval,  Bayesian computing, knowledge-based systems,
fuzzy methods, and  hybrid intelligent architectures.



Programme Structure
--------------
The following lectures/modules are available (at least modules with *
are intended to be available for the Oct. 2003 cohort entry)

Neural Networks *
Intelligent Systems Architectures *
Learning Agents *
Evolutionary Computation
Cognitive Neural Science *
Knowledge Based Systems and Data Mining *
Bayesian Computation
Vision and Intelligent Robots *
Natural Language Processing *
Dynamics of Adaptive Systems
Intelligent Systems Programming *


Funding up to 6000 pounds (about 9.000Euro) for eligible students
------------------------------

The Bursary Scheme applies to this Masters programme commencing
October 2003 and we have obtained funding through the European
Social Fund (ESF). ESF  support enables the University to waive the
normal tuition fee and provide  a bursary of £ 75 per week for 45 weeks
for eligible EU students,  together up to 6000 pounds or 9000 Euro.

For further information in the first instance please see:
http://www.his.sunderland.ac.uk/Teaching_frame.html
http://osiris.sund.ac.uk/webedit/allweb/courses/progmode.php?prog=G550A&mode=FT&\
mode2=&dmode=C

For information on applications and start dates contact:
         gillian.potts@...  Tel: 0191 515 2758
For academic information about the programme contact:
         alfredo.moscardini@...

Please forward to interested students.

Stefan

***************************************
Stefan Wermter
Professor for Intelligent Systems
Centre for Hybrid Intelligent Systems
School of Computing and Technology
University of Sunderland
St Peters Way
Sunderland SR6 0DD
United Kingdom

phone: +44 191 515 3279
fax:   +44 191 515 3553
email: stefan.wermter@...
http://www.his.sunderland.ac.uk/~cs0stw/
http://www.his.sunderland.ac.uk/
****************************************

Position open on bioinformatics/data mining for functional genomics -
deadline 31 August 2003
--------------------------------------------------------------------------------\
-------------
IOSI and IDSIA, Switzerland, are seeking for an outstanding person to work
for a new functional genomics facility. The position will offer the
opportunity to do top-level research on genomics, both at applied and
theoretical level, leading ultimately to establish a group of excellence in
bioinformatics with strong competence in data mining and molecular biology.
The functional genomics facility comprises an Affymetrix system and a
Packard/Perkin Elmer ScanArray Express scanner for spotted/customised
microarrays.

The work will be mainly based in the Experimental Oncology Department of
IOSI (Oncology Institute of Southern Switzerland, http://www.iosi.ch/),
inside the Institute for Research in Biomedicine
(http://www.irb.unisi.ch/), and at IDSIA (Dalle Molle Institute for
Artificial Intelligence, http://www.idsia.ch/).

Possible backgrounds are bioinformatics, computer science, physics,
engineering, mathematics, statistics, etc. The ideal candidate will have
either a Ph.D. in one of the former fields, or a M.Sc. degree followed by
2-3 years of experience with data mining and statistics. Strong skills in
Bayesian statistics and Bayesian network modelling would be a plus.
Knowledge of molecular biology and genomics is not required but preferred.
The ideal candidate will also be strongly skilled in computer science
(e.g., C, C++, Java programming, deep knowledge of common operating systems
such as Unix, Windows), and very experienced with data mining and
statistical packages.

The initial appointment will be for 2 years, starting in autumn 2003.
English is the official language at the Institute for Research in
Biomedicine and at IDSIA. See
http://www.idsia.ch/~zaffalon/positions/genomics03.htm for more information.


Applicants should submit:
(i) Detailed curriculum vitae
(ii) List of three references (and their email addresses)
(iii) Transcripts of undergraduate and graduate (if applicable) studies
(iv) Concise statement of their research interests (two pages max).

Please mail all correspondence to:

Prof. Franco Cavalli, Direttore Medico IOSI, Ospedale San Giovanni, 6500
Bellinzona, Switzerland.

Applications can also be submitted by fax (+41 (0)91 811 90 44) or by email
to oncosg@... (2MB max). WWW pointers to ps/pdf/doc/html files are
welcome. Use Firstname.Lastname.DocDescription.DocType for filename convention.

Thanks for your interest.

Franceso Bertoni, Responsible of the functional genomics/molecular
pathology unit, IOSI.
Marco Zaffalon, Senior researcher, IDSIA.

ABOUT IOSI
----------
Since 1988 the Division of Medical Oncology of the IOSI has had an active
research laboratory. The major goal of the laboratory has been to study the
biology and molecular genetics of lymphomas, in conjunction with the
clinical programs of bone marrow and peripheral stem cell transplantation.
All major molecular and cell biology techniques as well as
immunophenotyping of lymphoma and leukemia were established and are
currently employed in the laboratory. Researchers at the IOSI laboratory
began to study genetic and molecular rearrangements as diagnostic and
prognostic markers in non-Hodgkin's lymphomas (NHL). The laboratory has
been particularly active in the study of the biology of low-grade NHL, and
the pathogenesis of MALT lymphomas has been a major focus of the last few
years. With the expansion in laboratory space and personnel, new research
programs on solid tumours and molecular pharmacology have been initiated in
addition to the existing programs on NHL. These studies promise to shed
light into basic mechanisms of tumorigenesis and provide insights for
development of novel therapeutic and preventive strategies for cancer.
The overall goals of the laboratory's research programs in molecular
pathology and functional genomics are to analyze prognostic and diagnostic
molecular markers, identify predictive markers of response to therapeutic
and preventive agents, monitor pharmacodynamic responses to new agents in
clinical trials, and identify novel molecular therapeutic targets for
cancer disorders. These goals will be accomplished by using
state-of-the-art methodologies, including gene expression profiling by
microarray, conventional and real-time RT-PCR, genomic sequencing,
molecular cytogenetics, and immunohistochemistry.
In addition, the laboratory plans to establish, in conjunction with the
clinical research units, a tumour tissue bank of paraffin-embedded and
snap-frozen specimens from patients enrolled in all clinical trials carried
out at the IOSI. The laboratory is fully equipped to carry out all standard
cell biology and molecular biology techniques.
Dr. Catapano is the scientific director of the laboratory, while Dr.
Bertoni is responsible of the functional genomics/molecular pathology unit.
This unit currently consists of four investigators with expertise in the
areas of molecular biology, cytogenetics, microarray analysis. Other
laboratory personnel will assist and complement the molecular pathology
unit as needed.
All the equipment needed for more advanced genetic and molecular
biology-based research is also available, including ABI 310 nucleic acid
sequencer, ABI 7700 Real Time PCR, Affymetrix GeneChip system, Agilent
Bioanalyzer, Packard/PE ScanArray Express scanner for spotted microarrays
and arrayCGH, and BX61 Olympus system for classic and molecular (M-FISH)
cytogenetics.


ABOUT IDSIA
-----------
IDSIA (http://www.idsia.ch) is a joint research institute of the University
of Lugano (http://www.unisi.ch) and the Swiss Italian University for
Applied Science (http://www.supsi.ch). Our research focuses on uncertain
reasoning, imprecise probabilities, data mining, graphical models,
artificial neural nets, reinforcement learning, complexity and
generalization issues, unsupervised learning and information theory,
forecasting, artificial ants, combinatorial optimization, evolutionary
computation.
IDSIA is small but visible, competitive, and influential. The "X-Lab
Survey" by Business Week Magazine ranked IDSIA among the world's top ten
labs in Artificial Intelligence. IDSIA's algorithms hold the world records
for several important operations research benchmarks (see Nature
406(6791):39-42 for an overview of artificial ant algorithms developed at
IDSIA).
IDSIA is located near the swiss supercomputing center. IDSIA is close to
the beautiful city of Lugano in Ticino, the scenic southernmost province of
Switzerland. Zurich, Milan and Venice are only few hours away by train.

Our apologies if you receive multiple copies.

*********************************************************
********   LAST CALL FOR PAPERS ICCI 2003      **********
*********************************************************
****** THE DEADLINE HAS BEEN EXTENDED TO AUGUST 15 ******
*********************************************************

International Congress on Computational Intelligence

November 6-8, 2003, Medellín, Colombia

Home Page: http://www.unalmed.edu.co/~ciic/
Mirror Site: http://lslwww.epfl.ch/~acis/ciic03/


ICCI 2003

The International Congress on Computational Intelligence is a high-quality,
high-impact Computational Intelligence conference,  held this year at the
Universidad Nacional de Colombia at Medellin. The ICCI 2003 is organized by The
Colombian Network of Computational Intelligence, Red CIC, an international
organization dedicated to the promotion of scientific research and industrial
development in the Computational Intelligence area.

The upcoming meeting in this conference series follows the great success of ICCI
2001 held in the same place. The aim of ICCI 2003 is to bring together
researchers and practitioners from diverse fields, such as computer science,
information technology, business, education, human factors, system engineering,
electric-electronic engineering and industry to (1) examine the design
principles and performance characteristics of various approaches in
Computational Intelligence technology, and (2) increase the cross-fertilization
and applications of ideas on the development of Computational Intelligence 
systems in different domains in Colombia and Latin America. The nature of
Computational Intelligence is that there
is a wide diversity of techniques and applications and it is hoped that this
diversity will be exhibited in the papers accepted.

PAPERS

High-quality papers in all CI related areas are solicited. Papers exploring new
directions will receive a careful and supportive review. All submitted papers
will be reviewed on the basis of technical quality, relevance, significance, and
clarity.

To submit your manuscript take into account that:

* ICCI 2003 will accept ONLY on-line submission of papers, of up to 8 pages,
written in English or Spanish.
* The only accepted formats for submissions are Postscript or PDF formats.
* Instructions to format your paper are contained in
http://lslwww.epfl.ch/~acis/ciic03/ciic_authors.tgz.
* Please send your manuscripts to Carlos.Pena@...


After acceptance for presentation the papers will be published in the
proceedings.


TOPICS

The topics and areas to be addressed include, but not limited to:
*Adaptive computing
*Artificial life
*Autonomous societies
*Cellular Automatas
*Classifier systems
*Chaotic and fractal dynamics
*Coevolution
*Collective group behavior
*Complex behavior characterization and engineering
*Complex self-organized systems modelling and development
*Distributed intelligence
*Evolution and learning in dynamic environments
*Evolutionary computation
*Evolvable Hardware
*Emergent behavior
*Fuzzy Systems
*Hybrid Systems
*Machine Learning
*Molecular/DNA Computing
*Neural Networks
*Swarms

IMPORTANT DATES

August 1, 2003 (EXTENDED TO AUGUST 15!!): Electronic submission of full  papers

Sept. 2003: Notification of paper acceptance

October, 2003: Camera-ready copies of accepted papers

November 6-8, 2003: Conference & workshops/tutorials

Conference Chair:
Orlando Arcila
School of Mines, National University of Colombia at Medellin
oarcila@...

Program Chairs

Carlos A. Peña
Swiss Federal Institute of Technology
Laussane, Switzerland
Carlos.Pena@...

Oswaldo Velez-Langs
School of Engineering
Universidad Rey Juan Carlos
Madrid, Spain
ovelez@...

Program Commite

Alejandro Pazos,  Universidad de A Coruña, España
Andres Perez-Uribe, Ecole d'Ingénieurs du Canton de Vaud, Suisse
Andrés Upegui, Ecole Polytechnique Fédérale de Lausanne, Suisse
Annie Wu, University of Central Florida, USA
Carlos Coello, Cinvestav, México
Carlos Gershenson, Vrije Universiteit Brussel, Belgium
Edgar N. Sanchez, Cinvestav, México
Eduardo Caicedo, Universidad del Valle, Colombia
Eduardo Sanchez, Ecole Polytechnique Fédérale de Lausanne, Suisse
Ernesto Cuadros Vargas, Universidade de Sao Paulo, Brasil
Fernando Velez,  Université de la Sorbonne, France
Francisco Fernández de Vega, Universidad de Extremadura, España
Francisco Herrera, Universidad de Granada, España
Hector Fabio Restrepo Garcia, ELCA, Suisse
Humberto Loaiza, Universidad del Valle, Colombia
Jairo Espinosa, IPCOS, Belgium
Javier Dolado,  Universidad del Pais Vasco, España
Jesus Antonio Hernandez Riveros, Universidad Nacional - Medellín, Colombia
John William Branch, Universidad Nacional - Medellín, Colombia
Jorge Muruzabal, Universidad Rey Juan Carlos, España
Katya Rodriguez-Vasquez, UNAM - México
Lady Murrugarra, Universidad Peruana Cayetano Heredia
Max Garzón, University of Memphis, USA
Moshe Sipper, Ben Gurion University, Israel
Oscar Castillo, Instituto Tecnológico de Tijuana, México
Oscar Cordón, Universidad de Granada, España
Oscar Germán Duarte Velasco, Universidad Nacional - Bogotá, Colombia
Patricia Melin, Instituto Tecnológico de Tijuana, México
Rodolfo Soto Becerra, Instituto Colombiano del Petróleo, Colombia
Victor Hugo Grisales, Universidad Distrital Francisco José de Caldas, Colombia

Dear Colleagues: Two new draft works on Evolving Swarms for Data Mining,
which will soon be published in CEC'03 Congress on Evolutionary
Computation, Australia, can now be downloaded via the following links:

# Ajith Abraham*, Vitorino Ramos**, "Web Usage Mining using Artificial Ant
Colony Clustering and Genetic Programming",
http://alfa.ist.utl.pt/~cvrm/staff/vramos/ref_48.html .

# Vitorino Ramos**, Ajith Abraham*, "Swarms on Continuous Data",
http://alfa.ist.utl.pt/~cvrm/staff/vramos/ref_45.html .

Best regards, Vitorino
(*Oklahoma Univ., USA; **Technical Univ. of Lisbon, Portugal)

Please distribute:

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

    The 21st International Conference On Machine Learning (ICML-04)
                 July 4-8, 2004, Banff, Alberta, Canada

                      Call For Workshop Proposals

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

The ICML-2004 Organizing Committee invites proposals for workshops to
be held at the 21st International Conference on Machine Learning
(ICML-2004), which will take place July 4-8, 2004, in Banff, Alberta,
Canada. ICML-2004 will be co-located <http://www.banff04.org/> with
the Computational Learning Theory (COLT-04) and Uncertainty in AI
(UAI-04) conferences (see <http://www.banff04.org>). The workshops
will be held on July 8th, the same day as the UAI tutorials. There
will be room for two large (< 150 participants) and up to two small
workshops (< 40 participants).

Workshops provide organizers and participants with an opportunity to
focus intensively on a specific topic in machine learning. Workshops
can choose to concentrate on emerging research topics, but can also be
devoted to application issues, or to questions concerning the economic
and social aspects of Machine learning and data mining. Proposals that
aim at a cross-fertilization between Machine Learning and one of the
topics of the co-located conferences are particularly welcome.

Working notes of the workshops will be made available to participants
in electronic form prior to the conference.


       How to Propose a Workshop

Workshop proposals should contain the necessary information for the
workshop chair and reviewers from the conference organizing committee
to judge the importance, quality and community interest in the
proposed topic. Each workshop should have one or more designated
organizers and a workshop program committee. When proposing a
workshop, please provide (at least) the following information:

     * /Topic --/ What will the workshop be about? Why do you believe
       this is an interesting and significant topic? Why is the topic
       best addressed in an ICML workshop, as opposed to a workshop at
       another conference or papers in an ICML technical session?
     * /Goals --/ What do you expect will come out of the workshop? How
       will the workshop change the participants' understanding of the
       area? Do you think it will have an impact on the Machine Learning
       community at large?
     * /Intended audience --/ From which areas do you expect potential
       participants to come? How many participants do you expect? Can you
       already name some of them?
     * /Format --/ How will the workshop sessions be scheduled? How much
       time will be used for discussion, panel discussions, paper
       presentations, invited talks, or other methods for encouraging
       communication and consensus? Organizers are encouraged to focus on
       mechanisms other than traditional paper presentations and to
       differentiate themselves clearly from typical conference sessions.
     * /Publicity --/ How do you intend to publicize the workshop? How
       will you reach the most interested and appropriate participants?
       Are there any plans to document the workshop results (beyond
       ICML's web publication)?
     * /Organizers --/ Please include the name, postal address, phone
       number, e-mail address, and webpage of all members of the program
       committee. In addition, indicate the organizers' background in the
       workshop area.

Proposals should be submitted in electronic form to:

     Johannes Fuernkranz
     E-mail: juffi@...

Important Dates

     Dec 19, 2003  Proposal deadline
     Jan  7, 2004  Acceptance notification
     Jan 23, 2004  Publicity Materials Due
     Apr  2, 2004  WS Paper submission deadline
     Apr 16, 2004  Notification of participants
     May  7, 2004  WS final paper deadline
     May 14, 2004  Workshop notes due (on-line)

URL
     <http://www.oefai.at/icml-04/cfwp.html>.

Call for Papers: Workshop on Causality and Causal Discovery
(http://www.cs.uregina.ca/~causal04)

May 16th, in Conjunction with the Seventeenth Canadian Conference on
Artificial Intelligence (AI'2004). (http://cs.uwindsor.ca/~ai04).
University of Western Ontario, London, Ontario, Canada.


Background and Goals
  Is the relation between two events of a causal nature (one causes the
other) or an association? (they happen to be seen together, or have a
hidden common cause). Is it possible to answer this question in a reliable
manner? And if yes, what methods can be used?

  Causality and discovering causal relations are of interest because they
allow us to explain and control systems and phenomena. There have been
many debates on causality and if it is possible to discover causal
relations. There have been different approaches to solving the problem of
mining causality, such as utilising conditional probability or temporal
approaches. Discussing, evaluating, and comparing these methods can add
perspective to the efforts of all the people involved in this research
area. The aim of this workshop is to bring researchers from different
backgrounds together and discuss the latest work being done in this
domain.


Topics of interest include, but are not limited to the following:
Theoretical approaches for the discovery of causality
New algorithms and software for discovering causality
Adaptation of existing methods for causal discovery
Case studies and reports on practical applications
Philosophical considerations in the problem of discovering causality
Surveys of current approaches in the field of causal discovery


Submission of Papers
Prospective authors are invited to submit papers in any of the topics
listed above. The length of the papers is limited to 10 pages. The papers
will be in the same format as that of the Canadian AI conference (Springer
Verlag). Instructions for preparing the manuscript can be found at
http://www.springer.de/comp/lncs/authors.html

Please send papers in electronic form to causal04@...


Important Dates
Full paper submission deadline: Feb 9, 2004
Paper acceptance notification: Mar. 1, 2004
Final versions of accepted papers due: Mar. 31, 2004


Programme committee
Cory Butz, University of Regina
Eric Neufeld, University of Saskatchewan
Richard Scheines, Carnegie Melon University
Steven Sloman, Brown University


For more information please contact Kamran Karimi at karimi@...

Hi everybody,

  To people interested in discovering temporal/causal relations, or in
extracting classification rules from sequential data, or in generating
Prolog statements for automatic programme generation from observed patterns, I
recommend trying TimeSleuth version 2.5. As input it accepts sequences of
records, generated in a temporal or spatial order, and investigates whether
there is a relation among the fields, not only in a single record, but also
among many records. For example, it can detect if the value of a decision
attribute is determined by the condition attributes in previous,
next, or both previous and next, records.

  With TimeSleuth time can move in either forward or backward (or both)
directions. This property is used to distinguish between causal and acausal
relations.

  The TimeSleuth package includes executables for any platform with a Java
virtual machine, sources in Java, online help, example datasets, and
modified C4.5 sources (plus executables for Windows). It is availabe freely
from http://www.cs.uregina.ca/~karimi/downloads.html.

  If you have any questions, bug reports, or comments, please contact me at
karimi@....

Kamran Karimi

karimi@...
http://www.cs.uregina.ca/~karimi

Test =)
hgbyikyjoalynedvg
--
Test, yep.


[Non-text portions of this message have been removed]

Vitorino Ramos(*), Ajith Abraham(**), Evolving a Stigmergic Self-Organized
Data-Mining (recently submitted).
http://alfa.ist.utl.pt/~cvrm/staff/vramos/ref_50.html

ABSTRACT: Self-organizing complex systems typically are comprised of a
large number of frequently similar components or events. Through their
process, a pattern at the global-level of a system emerges solely from
numerous interactions among the lower-level components of the system.
Moreover, the rules specifying interactions among the system's components
are executed using only local information, without reference to the global
pattern, which, as in many real-world problems is not easily accessible or
possible to be found. Stigmergy, a kind of indirect communication and
learning by the environment found in social insects is a well know example
of self-organization, providing not only vital clues in order to understand
how the components can interact to produce a complex pattern, as can
pinpoint simple biological non-linear rules and methods to achieve improved
artificial intelligent adaptive categorization systems, critical for
Data-Mining. On the present work it is our intention to show that a new
type of Data-Mining can be designed based on Stigmergic paradigms, taking
profit of several natural features of this phenomenon. By hybridizing
bio-inspired Swarm Intelligence with Evolutionary Computation we seek for
an entire distributed, adaptive, collective and cooperative self-organized
Data-Mining. As a real-world / real-time test bed for our proposal,
World-Wide-Web Mining will be used. Having that purpose in mind, Web usage
Data was collected from the Monash University's Web site (Australia), with
over 7 million hits every week. Results are compared to other recent
systems, showing that the system presented is by far promising.

KEYWORDS: Self-organization, Stigmergy, Data-Mining, Linear Genetic
Programming, Distributed and Collaborative Filtering.

(*)  CVRM-IST, Technical Univ. Lisbon, PORTUGAL
(**) Natural Comp. Lab, Dep. Comp. Science, Oklahoma Univ, Tulsa, USA.

PLEASE ACCEPT OUR APOLOGIES IF YOU RECEIVE MULTIPLE COPIES

   
--------------------------------------------------------------------------------\
---------
    SWARM INTELLIGENCE AND PATTERNS (SIP'04) - Call for Papers
    Web site: http://alfa.ist.utl.pt/~cvrm/staff/vramos/SIP.html
   
--------------------------------------------------------------------------------\
---------

    Int. Workshop Session at ISDA'04 - 4th International
    Conference on Intelligent Systems,  Design and
    Applications.

    Conference dates: August 26-28, 2004.
            Location: Budapest,Hungary.

    Chairs:
    Vitorino Ramos (CVRM-IST, Technical University of Lisbon, PORTUGAL),
    Ajith Abraham (Bio-Inspired Grid Lab, Oklahoma State University, USA).
   
--------------------------------------------------------------------------------\
----------------

IMPORTANT DATES:

Paper submission Due (full paper) : April 1, 2004
Notification of acceptance: May 10, 2004
Camera ready papers and authors' registration : June 10, 2004
Conference - August 26-28, 2004. Budapest, Hungary.

SCOPE AND CALL FOR PAPERS:

Self-organizing intelligent complex systems typically are comprised of a
large number
of frequently similar components or events. Through their process, a
pattern at the
global-level of a system emerges solely from numerous interactions among
the lower-level
components of the system. Moreover, the rules specifying interactions among
the system's
components are executed using only local information, without reference to
the global pattern,
which, as in many real-world problems is not easily accessible or possible
to be found.
Stigmergy, a kind of indirect communication and learning by the environment
found in social
insects is a well know example of self-organization, providing not only
vital clues in order
to understand how the components can interact to produce a complex pattern
and engineer
applications, as can pinpoint simple biological non-linear rules and means
to achieve an
improved design of artificial intelligent systems.

SWARM INTELLIGENCE is precisely a relatively novel discipline devoted to
the study of
self-organizing collective processes in Nature and Human artefacts as well
as on their
applications. An example of particularly successful research direction in
swarm intelligence
is ant colony optimization (ACO), which focuses on discrete optimization
problems, and has
been applied successfully to a large number of hard discrete optimization
problems including
the travelling salesman, the quadratic assignment, scheduling, vehicle
routing, etc., as well
as to routing in telecommunication networks.

However, apart from the remarkable successful applications in optimization
as well as on their
critical features as a bio-inspired computational paradigm, a small number
of works have still
been devoted to Data Classification and Retrieval Systems, Clustering,
Pattern Recognition,
Distributed Data-Mining, Web Mining and GRIDS, Collaborative Filtering,
Image Analysis and
Signal Processing, Pattern Formation, Perception, Memory and Generalization.
At the present section we seek to explore the applicability of these
bio-inspired approaches
to the development of self-organizing, evolving, adaptive and autonomous
information technologies,
which will meet the requirements of next-generation information systems,
such as diversity,
scalability, robustness, and resilience.

TOPICS OF INTEREST:

Topics of interest include, but are not limited to, applications and theory
dealing with any
aspect of Swarm Intelligence, Pattern Recognition, Data and Image
Processing, as:

- Intelligent Systems Design.
- Advanced Signal and Image processing algorithms.
- Pattern Recognition and Emergent Behaviour.
- Data Categorization, Visualization. Data and Knowledge Extraction /
Representation.
- Feature Extraction and Selection. Unsupervised Learning.
- Information Systems.
- Collective Intelligence and Search. Exploring versus Exploiting.
- Artificial Habitats and Information.
- Exploratory Data Analysis. Data-Mining.
- Cognition, Interactivity, Signals and Communication.
- Bottom-up Strategies and Non-Hierarchical Systems.
- Adpative Systems and Self-Configuration.
- Mapping Concepts, Cognitive Maps and Self-Organizing Maps.
- Complex Adaptive Systems.
- Stigmergy, Self-Organization, Metamorphosis, Emergence and Co-Evolution.
- Artificial Life as well as other Animal Societies bio-inspired algorithms.
- Artificial Societies and Web-based Communities.
- Wireless Communication, Cellular Systems, Indirect Communication through
artefacts.
- Social Networks and New Media.
- Artificial Immune Systems and Self-Organization.
- Classification, Sorting, Data Retrieval, Clustering.
- Web Mining, Semantic Web, Collaborative Mining, GRIDS, Network security.
- Auto-Catalysis, Positive and Negative Feedbacks, Cybernetics.
- Swarm and Cooperative Robotics.
- Distributed algorithms, self-regulation, self-repair and self-maintenance
ontologies.
- Biomedical, multimedia and e-commerce applications.
- Collective on-line Games. iDesign, Active aLif(v)e Art and e-Artefacts.
- Generative and Computational Art.
- Hybridization with other methods (e.g. Evolutionary Computation and
Neural Networks).

PAPER SUBMISSION:

All accepted papers should follow IEEE format (check ISDA Call for Papers).
Submitted papers have to be original, 6 pages long, containing new and
original results.
Author's guidelines and format instructions can be downloaded from the
following links:
http://alfa.ist.utl.pt/~cvrm/staff/vramos/SIP.html and
http://www.cs.okstate.edu/~isda04/submission.html .
Please send the full paper as an email attachment to:
Vitorino Ramos
<mailto:vitorino.ramos@...>vitorino.ramos@... with
a cc to <mailto:ajith.abraham@...>ajith.abraham@... .

CONTACTS:
Vitorino Ramos: vitorino.ramos@...
[http://alfa.ist.utl.pt/~cvrm/staff/vramos]
Ajith Abraham: ajith.abraham@... [http://ajith.softcomputing.net/]

RELATED EVENTS:

# ANTS'2004 - 4th Int. Wkshp on ACO and Swarm Intelligence,
Brussels, Belgium, Sep 5-8 2004 [http://iridia.ulb.ac.be/~ants/ants2004/].
# ESOA'2004 - 2nd Int. Wkshp on Engineering Self-Organising Applications,
New York, USA, July 19 or 20 2004
[http://esoa.unige.ch/esoa04/esoa04-cfp.html].
# WCLC'2004 -1st World Congress on Lateral Computing,
Bangalore, India, Dec. 17-19 2004 [http://www.lateral-computing.org/wclc/].

PLEASE ACCEPT OUR APOLOGIES IF YOU RECEIVE MULTIPLE COPIES

   
--------------------------------------------------------------------------------\
---------
    SWARM INTELLIGENCE AND PATTERNS (SIP'04) - Call for Papers
    Web site: http://alfa.ist.utl.pt/~cvrm/staff/vramos/SIP.html
   
--------------------------------------------------------------------------------\
---------

    Int. Workshop Session at ISDA'04 - 4th International
    Conference on Intelligent Systems,  Design and
    Applications.

    Conference dates: August 26-28, 2004.
            Location: Budapest,Hungary.

    Chairs:
    Vitorino Ramos (CVRM-IST, Technical University of Lisbon, PORTUGAL),
    Ajith Abraham (Bio-Inspired Grid Lab, Oklahoma State University, USA).
   
--------------------------------------------------------------------------------\
----------------

IMPORTANT DATES:

Paper submission Due (full paper) : April 1, 2004
Notification of acceptance: May 10, 2004
Camera ready papers and authors' registration : June 10, 2004
Conference - August 26-28, 2004. Budapest, Hungary.

SCOPE AND CALL FOR PAPERS:

Self-organizing intelligent complex systems typically are comprised of a
large number
of frequently similar components or events. Through their process, a
pattern at the
global-level of a system emerges solely from numerous interactions among
the lower-level
components of the system. Moreover, the rules specifying interactions among
the system's
components are executed using only local information, without reference to
the global pattern,
which, as in many real-world problems is not easily accessible or possible
to be found.
Stigmergy, a kind of indirect communication and learning by the environment
found in social
insects is a well know example of self-organization, providing not only
vital clues in order
to understand how the components can interact to produce a complex pattern
and engineer
applications, as can pinpoint simple biological non-linear rules and means
to achieve an
improved design of artificial intelligent systems.

SWARM INTELLIGENCE is precisely a relatively novel discipline devoted to
the study of
self-organizing collective processes in Nature and Human artefacts as well
as on their
applications. An example of particularly successful research direction in
swarm intelligence
is ant colony optimization (ACO), which focuses on discrete optimization
problems, and has
been applied successfully to a large number of hard discrete optimization
problems including
the travelling salesman, the quadratic assignment, scheduling, vehicle
routing, etc., as well
as to routing in telecommunication networks.

However, apart from the remarkable successful applications in optimization
as well as on their
critical features as a bio-inspired computational paradigm, a small number
of works have still
been devoted to Data Classification and Retrieval Systems, Clustering,
Pattern Recognition,
Distributed Data-Mining, Web Mining and GRIDS, Collaborative Filtering,
Image Analysis and
Signal Processing, Pattern Formation, Perception, Memory and Generalization.
At the present section we seek to explore the applicability of these
bio-inspired approaches
to the development of self-organizing, evolving, adaptive and autonomous
information technologies,
which will meet the requirements of next-generation information systems,
such as diversity,
scalability, robustness, and resilience.

TOPICS OF INTEREST:

Topics of interest include, but are not limited to, applications and theory
dealing with any
aspect of Swarm Intelligence, Pattern Recognition, Data and Image
Processing, as:

- Intelligent Systems Design.
- Advanced Signal and Image processing algorithms.
- Pattern Recognition and Emergent Behaviour.
- Data Categorization, Visualization. Data and Knowledge Extraction /
Representation.
- Feature Extraction and Selection. Unsupervised Learning.
- Information Systems.
- Collective Intelligence and Search. Exploring versus Exploiting.
- Artificial Habitats and Information.
- Exploratory Data Analysis. Data-Mining.
- Cognition, Interactivity, Signals and Communication.
- Bottom-up Strategies and Non-Hierarchical Systems.
- Adpative Systems and Self-Configuration.
- Mapping Concepts, Cognitive Maps and Self-Organizing Maps.
- Complex Adaptive Systems.
- Stigmergy, Self-Organization, Metamorphosis, Emergence and Co-Evolution.
- Artificial Life as well as other Animal Societies bio-inspired algorithms.
- Artificial Societies and Web-based Communities.
- Wireless Communication, Cellular Systems, Indirect Communication through
artefacts.
- Social Networks and New Media.
- Artificial Immune Systems and Self-Organization.
- Classification, Sorting, Data Retrieval, Clustering.
- Web Mining, Semantic Web, Collaborative Mining, GRIDS, Network security.
- Auto-Catalysis, Positive and Negative Feedbacks, Cybernetics.
- Swarm and Cooperative Robotics.
- Distributed algorithms, self-regulation, self-repair and self-maintenance
ontologies.
- Biomedical, multimedia and e-commerce applications.
- Collective on-line Games. iDesign, Active aLif(v)e Art and e-Artefacts.
- Generative and Computational Art.
- Hybridization with other methods (e.g. Evolutionary Computation and
Neural Networks).

PAPER SUBMISSION:

All accepted papers should follow IEEE format (check ISDA Call for Papers).
Submitted papers have to be original, 6 pages long, containing new and
original results.
Author's guidelines and format instructions can be downloaded from the
following links:
http://alfa.ist.utl.pt/~cvrm/staff/vramos/SIP.html and
http://www.cs.okstate.edu/~isda04/submission.html .
Please send the full paper as an email attachment to:
Vitorino Ramos
<mailto:vitorino.ramos@...>vitorino.ramos@... with
a cc to <mailto:ajith.abraham@...>ajith.abraham@... .

CONTACTS:
Vitorino Ramos: vitorino.ramos@...
[http://alfa.ist.utl.pt/~cvrm/staff/vramos]
Ajith Abraham: ajith.abraham@... [http://ajith.softcomputing.net/]

RELATED EVENTS:

# ANTS'2004 - 4th Int. Wkshp on ACO and Swarm Intelligence,
Brussels, Belgium, Sep 5-8 2004 [http://iridia.ulb.ac.be/~ants/ants2004/].
# ESOA'2004 - 2nd Int. Wkshp on Engineering Self-Organising Applications,
New York, USA, July 19 or 20 2004
[http://esoa.unige.ch/esoa04/esoa04-cfp.html].
# WCLC'2004 -1st World Congress on Lateral Computing,
Bangalore, India, Dec. 17-19 2004 [http://www.lateral-computing.org/wclc/].

Please distribute:

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

     The 21st International Conference On Machine Learning (ICML-04)
                  July 4-8, 2004, Banff, Alberta, Canada

                      Tutorial and Workshop Program

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

The following workshops and tutorials will be held at the 21st
International Conference on Machine Learning:

Tutorials
=========

Morning Tutorials

      * M1: The Many Faces of ROC Analysis in Machine Learning
            o Peter Flach (University of Bristol)

      * M2: Bayesian Methods for Machine Learning
            o Zoubin Ghahramani (University College London)

      * M3: Spectral Clustering
            o Chris Ding (Lawrence Berkeley National Laboratory)

      * M4: Game-theoretic Learning
            o Amy Greenwald (Brown University)

Afternoon Tutorials

      * A1: Junk E-mail Filtering
            o Geoff Hulten (Microsoft Research)
            o Joshua Goodman (Microsoft Resarch)

      * A2: Kernels for Structured Data
            o Thomas Grtner (Fraunhofer Institut AIS)

      * A3: Probabilistic Logic Learning
            o James Cussens (University of York)
            o Kristian Kersting (Albert-Ludwigs University of Freiburg)

      * A4: Data Structures for Fast Statistics
            o Alexander Gray (Carnegie Mellon University)
            o Andrew Moore (Carnegie Mellon University)

The tutorials will be held on the first day of the conference, July
4th, 2004. Tutorial fees are included in the ICML registration, but
they can also be attended independent of the conference. More details
can be found at http://www.oefai.at/icml-04/tutorials.html


Workshops
=========

      * Predictive Representations of World Knowledge
        Organizers:
            o Rich Sutton (University of Alberta)
            o Satinder Singh (University of Michigan)

      * Relational Reinforcement Learning
        Organizers:
            o Prasad Tadepalli (Oregon State University)
            o Robert Givan (Purdue University)
            o Kurt Driessens (Catholic University of Leuven)

      * Statistical Relational Learning
        Organizers:
            o Tom Dietterich (Oregon State University)
            o Lise Getoor (University of Maryland)
            o Kevin Murphy (MIT)

      * Physiological Data Modeling - A Competition
        Organizers:
            o David Andre (Bodymedia, Inc.)
            o Peter Stone (University of Texas, Austin)


The first three workshops will have the following joint paper
submission deadlines.

      Apr 2, 2004  WS Paper submission deadline
      Apr 16, 2004  Notification of participants
      May 7, 2004  WS final paper deadline

The workshops will be held on July 8th, the last day of the
conference. Workshop fees are not included in the regular conference
fees. The workshops can also be attended independent of the main
conference. More details can be found at
http://www.oefai.at/icml-04/workshops.html.

Hi all,

  TimeSleuth 3.0, a software for discovering causal and acausal rulesets,
has been released. It takes as input a sequence of observed attributes,
and provides tests to determine the nature of the relationship (causal,
acausal, or instantaneous)  among a decision attribute and the condition
attributes.

In TimeSleuth time can move from the past to the present, from the
future to the present, or a in both directions simultaneously.

  TimeSleuth version 3.0 removes some bugs and add a statistical test
that helps the user determine the type of relationship. It can be
downloaded from http://www.cs.uregina.ca/~karimi/downloads.html.
TimeSleith is written in Java. The package includes sources,
executables, example input files, and online help.

Please let me know if you have any problems or comments.

Kamran Karimi
karimi@...
http://www.cs.uregina.ca/~karimi

Argh,  i don't  like the  plaintext  :)

password: 43267


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