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ROKS 2013 : International workshop on advances in Regularization, Optimization, Kernel methods and Support vector machines: theory and applications

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Link: http://www.esat.kuleuven.be/sista/ROKS2013
 
When Jul 8, 2013 - Jul 10, 2013
Where Leuven, Belgium
Submission Deadline Mar 11, 2013
Notification Due Apr 8, 2013
Categories    machine learning   optimization   statistics   systems
 

Call For Papers

UPDATE:
Videos available at
http://videolectures.net/roks2013_leuven/


UPDATE: DEADLINE EXTENSION
March 11 (hard deadline)


ROKS-2013

International workshop on advances in Regularization, Optimization, Kernel methods and Support vector machines: theory and applications

July 8-10, 2013, Leuven, Belgium
http://www.esat.kuleuven.be/sista/ROKS2013

SCOPE

One area of high impact both in theory and applications is kernel methods and support vector machines. Optimization problems, learning and representations of models are key ingredients in these methods. On the other hand considerable progress has also been made on regularization of parametric models, including methods for compressed sensing and sparsity, where convex optimization plays a prominent role. The aim of ROKS-2013 is to provide a multi-disciplinary forum where researchers of different communities can meet, to find new synergies along these areas, both at the level of theory and applications.

The scope includes but is not limited to:
- Regularization: L2, L1, Lp, lasso, group lasso, elastic net, spectral regularization, nuclear norm, others
- Support vector machines, least squares support vector machines, kernel methods, gaussian processes and graphical models
- Lagrange duality, Fenchel duality, estimation in Hilbert spaces, reproducing kernel Hilbert spaces, Banach spaces, operator splitting
- Optimization formulations, optimization algorithms
- Supervised, unsupervised, semi-supervised learning, inductive and transductive learning
- Multi-task learning, multiple kernel learning, choice of kernel functions, manifold learning
- Prior knowledge incorporation
- Approximation theory, learning theory, statistics
- Matrix and tensor completion, learning with tensors
- Feature selection, structure detection, regularization paths, model selection
- Sparsity and interpretability
- On-line learning and optimization
- Applications in machine learning, computational intelligence, pattern analysis, system identification, signal processing, networks, datamining, others
- Software


INVITED SPEAKERS

Francis Bach, INRIA
Stephen Boyd, Stanford University
Martin Jaggi, Ecole Polytechnique Paris
James Kwok, Hong Kong University of Science and Technology
Yurii Nesterov, Catholic University of Louvain UCL
Massimiliano Pontil, University College London
Justin Romberg, Georgia Tech
John Shawe-Taylor, University College London
Bernhard Schoelkopf, Max Planck Institute Tuebingen
Joel Tropp, California Institute of Technology
Ding-Xuan Zhou, City University of Hong Kong


CALL FOR ABSTRACTS

The ROKS-2013 program will feature invited plenary talks, oral sessions and poster sessions. Interested participants are cordially invited to submit an extended abstract (max. 2 pages) for their contribution. After the workshop a number of selected contributions will be invited for an edited book.

For further information see http://www.esat.kuleuven.be/sista/ROKS2013 .

IMPORTANT DATES

- Deadline extended abstract submission: March 4, 2013
- Notification of acceptance: April 8, 2013
- Deadline for registration: June 3, 2013
- International Workshop ROKS-2013: July 8-10, 2013

ORGANIZING COMMITTEE

Chair: Johan Suykens (KU Leuven)

Andreas Argyriou (Ecole Centrale Paris), Kris De Brabanter (KU Leuven), Moritz Diehl (KU Leuven), Kristiaan Pelckmans (Uppsala University), Marco Signoretto (KU Leuven), Vanya Van Belle (KU Leuven), Joos Vandewalle (KU Leuven)

Co-sponsored by ERC Advanced Grant

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