Connectionists: Call for papers Special Session on 'High dimensional data analysis - theoretical advances and applications' at CIDM 2014 / SSCI

[Frank-Michael Schleif]

Call for Papers

Special Session on

'High dimensional data analysis -
theoretical advances and applications'

09-12 December 2014, Orlando, Florida, USA
http://www.ieee-ssci.org/CIDM.html
http://www.cs.bham.ac.uk/~schleify/CIDM_2014/

AIMS AND SCOPE

Modern measurement technology, greatly enhanced storage capabilities
and novel data formats have radically increased the amount and
dimensionality of electronic data. Due to its high dimensionality,
complexity and the curse of dimensionality, these data sets can often
not be addressed by classical  statistical methods. Prominent examples
can be found in the life sciences  with microarrays, hyper spectral
data in geo-sciences but also in fields like astrophysics, biomedical
imaging, finance or web and market basket analysis.

Computational intelligence methods have the potential to be used to
pre-process,  model and to analyze such complex data but new
strategies are needed to get efficient  and reliable models. Novel
data encoding techniques and projection methods, employing  concepts
of randomization algorithms have opened new ways to obtain compact
descriptions
of these complex data sets or to identify relevant information.
However theoretical  foundations and the practical potential of these
methods and alternative approaches  has still to be explored and
improved. New advances and research to address the curse  of
dimensions, and to uncover and exploit the blessings of high
dimensionality in data  analysis are of major interest in theory and
application.

TOPICS
This workshop aims to promote new advances and research directions to
address  the modeling, representation/encoding and reduction of
high-dimensional data or  approaches and studies adressing challenging
problems in the field of high dimensional data analysis. Topics of
interest range from theoretical foundations, to algorithms and
implementation,
to applications and empirical studies of mining high dimensional data,
including (but not limited to) the following:

o Studies on how the curse of dimensionality affects computational
intelligence methods
o New computational intelligence techniques that exploit some
properties of high dimensional data spaces
o Theoretical findings addressing the imbalance between high
dimensionality and small sample size
o Stability and reliability analyses for data analysis in high dimensions
o Adaptive and non-adaptive dimensionality reduction for noisy high
dimensional data sets
o Methods of random projections, compressed sensing, and random matrix
theory applied to high dimensional data mining
o Models of low intrinsic dimension, such as sparse representation,
manifold models, latent structure models, and studies of their noise
tolerance
o Classification, regression, clustering of high dimensional complex data sets
o Functional data mining
o Data presentation and visualisation methods for very high
dimensional data sets
o Data mining applications to real problems in science, engineering or
businesses where the data is high dimensional

PAPER SUBMISSION
High quality original submissions (upto 8 pages, IEEE style) should
follow the guidelines as outlined at the CIDM homepage
and should be submitted using the provided IEEE paper submission
system. We strongly encourage to
use the LaTeX stylesheet and not the word format to ensure high
quality typesetting and paper representation
also during the review process.

Webpage of the special session: http://www.cs.bham.ac.uk/~schleify/CIDM_2014/

IMPORTANT DATES
Paper submission deadline : 15 June 2014
Notification of acceptance : 05 September 2014
Deadline for final papers : 05 October 2014

The CIDM 2014 conference : 9-12 December 2014

SPECIAL SESSION ORGANIZERS:
Ata Kaban, University of Birmingham, Birmingham, UK
Frank-Michael Schleif, University of Birmingham, Birmingham, UK
Thomas Villmann, University of Appl. Sc. Mittweida, Germany