[compgeom-announce] Topological Learning workshop

["michael.aupetit@cea.fr" <michael.aupetit@cea.fr>]

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    The first international Workshop on topological learning
		       In conjunction with ISMIS 2009
		http://eric.univ-lyon2.fr/~topolearn/
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CALL FOR PAPER

There is a growing interest in learning data topology, from theoretical results
to real-world applications. 
Topological learning is an emerging field which is expected to bring new
insights in all the areas of the data mining and knowledge discovery process. 

Data mining and knowledge discovery (KDD), as stated in their early definition,
can today be considered as stable fields with numerous efficient methods and
studies that have been proposed to extract knowledge from data. In every data
mining task, understanding the structure of multidimensional patterns, in
supervised or unsupervised cases, is of fundamental importance. 
Topological learning aims at finding hidden structures (usually low-dimensional
manifolds) in order to better understand and exploit data.

The aim of this workshop is to address issues related to the concepts of
learning data topology. Our goal is to attract papers dealing with each step of
this field. Actually, learning data topology within the KDD process implies to
work on every step, starting from the pre-processing (e.g. structuring and
organizing) to the visualization and interpretation of the results, via the
data mining methods themselves. 

There are still big practical and theoretical challenges dealing with data
topology, among which: how to deal with noisy, high-dimensional, multi-scale or
complex data (times series, images, graphs, trees, texts, etc.)? How to
interpret and qualify the results?  How to select the models complexity? How to
design efficient algorithms with theoretical guarantees? When is topological
learning beneficial against usual methods? Etc. Papers dealing with these
issues and reporting applications on real data will be of fundamental interest
for this emerging field, and will take high priority for the selection process.


KDD fields which involve topological learning, include, but are not limited to:

      - Topology learning
      - Manifold learning
      - Spectral clustering and embedding
      - Spectral feature selection
      - Linear and non linear dimensionality reduction
      - Computational topology
      - Mathematical morphology
      - Geometric Inference
      - Topological learning and complex data
      - Applications and experience feedback

More and more people approach the field of topological learning from different
and interesting angles. They come from various communities such as data mining,
statistics, geometry, topology, physics, medicine or engineering. We believe
that now is the right time to establish and enhance cross fertilization between
these communities. 

During this workshop, researchers will have the opportunity to bring new ideas,
discuss their experiences and contribute to the theoretical and practical
maturation of topological learning. 

The workshop will consist in a series of communications (oral presentations or
poster). A reasonable time will be left for the discussion after each
presentation. 

All the articles will be reviewed at least twice with a goal to improve their
quality and give advice to the authors. A dedicated place will be given to the
young researchers with a session (Position paper) grouping the work in progress
in the various European teams. That can be the occasion for a PhD student or a
young researcher to present his/her starting project. 

This session will be particularly significant for work on the beginning and the
installation of research groups on shared topics. Demonstrations of research
results could be associated with the poster presentations.

INTRUCTIONS FOR AUTHORS 

The submissions should be written in English and should not exceed 10 pages in
the Springer Verlag format.

Submitted papers will be evaluated by at least three reviewers. 

Any submission that exceeds length limits or deviates from formatting
requirements may be rejected without review.

IMPORTANT DATES

Abstract submission June 1, 2009
Paper submission June 7, 2009
Notifications July 12, 2009
Camera-ready version July 31, 2009
Workshop September 14, 2009 

PROGRAM CHAIRS

      - MichaÃl AUPETIT, CEA, LIST, Saclay, France
      - Hakim HACID, Alcatel-Lucent Bell Labs, France
      - Djamel A. ZIGHED, University of Lyon 2, France 

PROGRAM COMMITTEE (to be completed..)

      - MichaÃl AUPETIT, CEA, LIST, Saclay, France
      - YounÃs BENNANI, Univ. Paris 13, Paris, France 
      - Stephane BONNEVAY, Univ. Lyon 1, France 
      - Marc BUI, EPHE, Paris 
      - FrÃdÃric CHAZAL, INRIA, Orsay, France 
      - David COHEN-STEINER, INRIA, Orsay, France 
      - Marie COTRELL, Univ. Dauphine, Paris, France 
      - Pierre GAILLARD, CEA, DAM, Arpajon, France 
      - Hakim HACID, Alcatel-Lucent Bell Labs, France 
      - Michel LAMURE, Univ. Lyon 1, France 
      - John LEE, UCL, Louvain-la-Neuve, Belgium 
      - Sylvain LESPINATS, CEA, LIST, Saclay, France 
      - Thomas MARTINETZ, Univ. of Luebeck, Germany  
      - Mikhail BELKIN, The Ohio State University, USA	
      - Steve OUDOT, INRIA, Orsay, France 
      - Fabrice ROSSI, ENST, Paris, France 
      - Vin de SILVA, Pomona College, California, USA 
      - Michel VERLEYSEN, UCL, Louvain-la-Neuve, Belgium 

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