[Elsnet-list] CFP : Teaching Machine Learning (TML 2008)

Jean.Christophe.Janodet at univ-st-etienne.fr Jean.Christophe.Janodet at univ-st-etienne.fr
Fri Feb 22 17:58:49 CET 2008

*Apologies for cross-posting. Please forward to interested people*

                        Call for Papers
       Workshop on Teaching Machine Learning (TML 2008)


               Saint-Etienne, 5-7 May 2008

Under the auspices of the PASCAL 2 Network of Excellence and the
University of Saint-Etienne

Machine Learning has been developing as a research topic with many
applications and ramifications to other fields during the past few years.
This has led to seeing the research activities in Machine Learning
organised by major conferences, journals and networks. Today, having a
background in Machine Learning is a major asset for students, whether to
apply for academic or industrial positions. Yet, very little focused
attention has been played on the question of how these students were to
receive this background.

Important questions such as the following have up to now only received
local attention:
- At what level should machine learning be taught?
- What experience do we have? Who is teaching machine learning?
- Due to the many links with mathematics, algorithmics, applications
  (linguistics, biology, etc), but also to the strong experimental
component, who should the targeted students be? What background should
they have?
- What material (books, software, benchmarks, video-lectures, world wide
web) can we find today for teaching machine learning?

The PASCAL 2 NOE, following on initiatives like the machine learning
summer schools, the analysis of patterns schools and the PASCAL bootcamp,
proposes to help coordinate the energies over this question.

The aim of the TML 2008 workshop is to bring together researchers and
practitioners that are interested in the teaching and education aspect of
the field. A particular attention will be kept for the Masters level,
which is felt to be the possible place where leverage is best and where
the tools that can be provided today by the European Union in order to
build collaborative courses over different countries are best suited.

Researchers, practitioners and educators are invited to contribute to and
participate in the workshop.

Scope :

The workshop will address issues specific to Teaching Machine Learning
including, but not restricted to:
- innovative approaches to learning and teaching ML
- approaches for improving the students' learning experience
  (Undergraduate and/or Graduate)
- incorporating ML research into ML courses
- the integration of theory and practice
- tools for supporting teaching and learning ML
- ML applications to assist in class instruction

Paper submissions :

The deadline for submitting abstracts/papers is the 31st of March. The
conditions for submissions are best explained on the workshop webpage.
Authors of accepted papers should use the proposed templates for
formatting their paper (6 pages maximum).

Important dates :

- Submissions due: March 31st
- Notification of acceptance: April 10th
- Camera-ready copy due: April 30th
- Workshop: May 5-7, Saint-Etienne-France

Registration :

If you would like to attend the workshop, please send a brief paragraph
describing your interests in the area to Colin de la Higuera
(cdlh at univ-st-etienne.fr) by the 15th April 2008. Upon acceptance, you
will be able to register online via the website before the 15th of April
2008. To register for the workshop follow the link "registration" from the
website. Late registration (after the 15th of April) will require the
payment of a registration fee.

Organiser :

The workshop will be organised by the computer science team at Laboratoire
Hubert Curien, University of Saint-Etienne. Email:
tml08 at univ-st-etienne.fr

Program Committee :

Jose Balcazar, UPC, Barcelona
Nello Christianini, University of Bristol
Ricard Gavalda, UPC, Barcelona
Marko Grobelnik, JSI, Ljubljana
Mark Herbster, UCL, London
Sami Kaski, TKK, Helsinki
Dunja Mladenic, JSI, Ljubljana
Luisa Mico, Universidad de Alicante
Gunnar Raetsch, Max Planck institute , Tübingen
Bernhard Scholkopf, Max Planck Institute, Tübingen
Marc Sebban, University of Saint-Etienne
John Shawe-Taylor, UCL, London

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