============================================================================================
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

URL:http://ama.liglab.fr/ieeeBigDataWorkshop/


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

DESCRIPTION
-----------------------

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

SUBMISSION
---------------------

Please submit your electronic submissions at

https://wi-lab.com/cyberchair/2013/bigdata13/scripts/submit.php?subarea=SA&undisplay_detail=1&wh=/cyberchair/2013/bigdata13/scripts/ws_submit.php

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.


Organizers:
---------------------
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 Grenoble




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