posted by system || 2375 views || tracked by 6 users: [display]

FDTop 2009 : 1st Workshop on Topological Learning

FacebookTwitterLinkedInGoogle

Link: http://eric.univ-lyon2.fr/~fdtop
 
When Jan 27, 2009 - Jan 27, 2009
Where Strasbourg, France
Abstract Registration Due Nov 15, 2008
Submission Deadline Nov 30, 2008
Notification Due Dec 10, 2008
Final Version Due Dec 20, 2008
Categories    machine learning   knowledge discovery
 

Call For Papers

************************************************************************
The 1st Workshop on Topological Learning
In conjunction with EGC'2009
January 27, 2009
Strasbourg, France
http://eric.univ-lyon2.fr/~fdtop/
********************************************************************

INTRODUCTION

There is a growing interest in learning data topology, from theoretical results to real-world applications. Topological learning is a very large field including manifold learning, computational geometry, etc. This workshop aims to bring new ideas and research fields to the area of topological learning.

Data mining and knowledge discovery, 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 case, is of fundamental importance. Topological learning aims at finding hidden structures (usually low-dimensional manifolds) in order to better understand and exploit data.

TOPICS

The aim of this workshop will be to address issues related to the concepts of learning data topology. Our goal will be 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 preprocessing (e.g. structuring and organizing) to the visualization and interpretation of the results, via the data mining methods themselves. Papers will be invited on all the KDD fields which involve topological learning, including, but not limited to:

- Topology learning
- Manifold learning
- Spectral clustering and embedding
- Spectral feature selection
- Linear and non linear dimensionality reduction
- Computational geometry (morphology)
- Topological learning and complex data
- Applications and experience feedback

More and more people approach the filed of topological learning from different and interesting angles. They come from various communities such as data mining, mathematics, physics, medicine and engineering. We believe that now is the right time to establish and enhance communication between these communities.

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.

INSTRUCTIONS TO AUTHORS

Papers submitted could be in english or french language and should not exceed 12 pages in the RNTI-column format (see http://www.antsearch.univ-tours.fr/publi/RNTI-X-Y.zip) )

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 November 15, 2008
- Paper submission November 30, 2008
- Notifications December 10, 2008
- Camera-ready version December 20, 2008
- Workshop January 27, 2009

COMMITTEES

Workshop chairs
- Djamel A. Zighed, University of Lyon 2, France
- Hakim Hacid, University of New South Wales, Australia

Program Committee (to be completed..)
- Micha?l Aupetit, CEA-DAM, Departement Analyse Surveillance Environnement, France
- Youn?s Bennani, University Paris 13, France
- Marc Bui, Ecole Pratique des Hautes Etudes, Paris, France
- Gilles Venturini, University of Tours, France
- Pierre Gaillard, CEA-DAM, D?partement Analyse Surveillance Environnement, France
- Hakim Hacid, University of new South Wales, Australia
- Pascale Kuntz-Cosperec, University Nantes, France
- Michel Lamure, University of Lyon1, France
- S?bastien Lef?vre, University Louis Pasteur, Strasbourg 1, France
- Fabrice Muhlenbach, University of St Etienne, France
- Taimur Qureshi, University Lyon 2, France
- Vincent Pisetta, University Lyon 2, France
- St?phane Lallich, University Lyon 2, France
- Djamel A Zighed, University Lyon 2, France

Related Resources

IARCE 2021-Ei Compendex & Scopus 2021   2021 5th International Conference on Industrial Automation, Robotics and Control Engineering (IARCE 2021)
ICDM 2021   21th Industrial Conference on Data Mining
SI-DAMLE 2020   Special Issue on Data Analytics and Machine Learning in Education
ML_BDA 2021   Special Issue on Machine Learning Technologies for Big Data Analytics
MLDM 2021   17th International Conference on Machine Learning and Data Mining
20th ICTEL October, Dubai 2021   20th ICTEL 2021 – International Conference on Teaching, Education & Learning, 23-24 October, Dubai
WSPML 2020   2020 2nd International Workshop on Signal Processing and Machine Learning (WSPML 2020)
Fintech 2020   Sustainaility (Q2): Fintech: Recent Advancements in Modern Techniques, Methods and Real-World Solutions
TERA - Eurasia Research 2021   19th ICTEL 2021 – International Conference on Teaching, Education & Learning, 11-12 October, Lisbon
ACM--ICMLSC--EI Compendex, Scopus 2021   ACM--2021 The 5th International Conference on Machine Learning and Soft Computing (ICMLSC 2021)--EI Compendex, Scopus