Connectionists: special session on Learning and Modelling Big Data
Barbara Hammer
bhammer at techfak.uni-bielefeld.de
Thu Sep 19 04:08:34 EDT 2013
*** Apologies for cross posting ***
Special Session on Learning and Modeling Big Data
at ESANN 2014, 23-25 April 2014, Bruges, Belgium, http://www.esann.org
Organizers: Barbara Hammer (Bielefeld University, DE), Haibo He (Rhode
Island, USA), Thomas Martinetz (University of Luebeck, DE)
Abstract:
Big data in the sense of large or streaming data sets, very high
dimensionality, or complex data formats constitute one of the major
challenges faced by machine learning today, caused by powerful sensors
and digitalization techniques as well as dramatically increased storage
capabilities. In this realm, a couple of typical assumptions of machine
learning can no longer be met, causing the need for novel algorithmic
developments and paradigm shifts, such as
* online learning and techniques for streaming data
* learning from non i.i.d. data and skewed distributions
* life-long adaptation of model complexity and hyper-parameters
* linear or sublinear algorithms with limited online memory capacity
* parallel implementations
* sparse representation of data, efficient information compression
* interpretable models
* learning from the crowd
* good priors in the context of extremely high dimensionality
We solicit contributions focussing on novel algorithmic developments,
theoretical investigations or applications connected to this
non-exhaustive list of topics.
Schedule:
Paper submission deadline : 29 November 2013
Notification of acceptance : 31 January 2014
Deadline for final papers : 21 February 2014
ESANN 2014 conference : 23-25 April 2014
Infos on submissions can be found at http://www.esann.org
--
Prof. Dr. Barbara Hammer
CITEC centre of excellence
Bielefeld University
D-33594 Bielefeld
Phone: +49 521 / 106 12115
Fax: +49 521 / 106 12181
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