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Subject: [ E-CFP ] Workshop on New Learning Frameworks and Models for BigDat
From: <Massih-Reza.Amini_(on)_imag.fr>
Date received: 05 Jul 2013
Deadline: -
Start date: 06 Oct 2013

Workshop on New Learning Frameworks and Models for BigData -
Submission deadline: 07/30/2013

Workshop at IEEE international conference on BigData 6 October
2013, Silicon Valley, USA


Important Dates
*****Workshop paper submission deadline: July 30, 2013
*****Workshop paper acceptance notification: August 20, 2013
*****Workshop paper camera-ready deadline: September 10, 2013


Huge amounts of data are now easily and legally available on the
Web. This data is generally heterogeneous and merely structured.
Machine learning models which have been developed to
automatically retrieve, classify or cluster observations on large
yet homogeneous data collections have to be rethought. Indeed,
many challenging problems, inevitably associated to Big Data,
have manifested the needs for tradeoffs between the two
conflicting goals of speed and accuracy. This has led to some
recent initiatives in both theory and practice and has highly
motivated the interest of the Machine Learning community. Further
theoretical challenges include how to tackle problems with large
number of target classes, appropriate optimization techniques to
handle big data problems. Structured/sequential prediction models
for big data problems such as prediction in hierarchy of classes
has also gained importance in recent years.

The goal of this workshop is to bring together research studies
aiming at developing new machine learning tools to handle new
challenges associated to Big Data mining. We are especially
interested on the following topics:

        Distributed on-line learning Multi-task learning for big
        data Transfer Learning for big data Optimization
        techniques for large-scale learning Handling large number
        of target classes in big data Structured prediction
        models in big data Speed/Accuracy tradeoffs in big data
        Statistical inference for big data Noise in Big data


Please submit your electronic submissions at


no later than July the 30th, 2013. All papers accepted for
workshops will be included in the Workshop Proceedings published
by the IEEE Computer Society Press, made available at the
Conference. All submissions must be in PDF format and particular
care should be taken to ensure that your paper prints well. Some
accepted papers will be selected for edition into a book.

Massih-Reza Amini: Laboratoire d'Informatique de Grenoble,
University of Grenoble Rohit Babbar: Laboratoire d'Informatique
de Grenoble, University of Grenoble Eric Gaussier: Laboratoire
d'Informatique de Grenoble, University of Grenoble Ioannis
Partalas: Laboratoire d'Informatique de Grenoble, University of

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