Connectionists: IJCNN 2017 SPECIAL SESSION on "Large Datasets and Big Data Analytics"

[Luca Oneto]

[Apologies if you receive multiple copies of this CFP]

Call for papers: special session on "Large Datasets and Big Data Analytics:
Theory, Methods, and Applications" at IJCNN 2017

International Joint Conference on Neural Networks (IJCNN 2017).
14-19 May 2017, Anchorage, Alaska, USA - http://www.ijcnn.org/

DESCRIPTION:
The information age brings along an exponentially growing quantity of
heterogeneous data from multiple sources in every aspect of our lives: data
coming from social networks, internet of things, experiments in biology
research and data from transportation systems are only a few examples.
Recent trends in the area suggest that in the coming years the exponential
data growth will continue, and that there is a strong need to find
efficient solutions to deal with aspects such as data wrangling, real-time
processing, information extraction and abstract model generation.
Large datasets and big data analytics is the area of research focused on
collecting, examining and processing large multi-structure, multi-modal,
and multi-source datasets in order to discover patterns, correlations and
extract information from data. In order to be able to perform such an
analysis, conventional technologies and machine learning theory and
algorithms are not directly applicable because they are not able to deal
efficiently and effectively with such amount of data. Thus, specific
techniques have to be developed.
The purpose of this special session is to highlight recent advances in the
field of large datasets and big data analytics. In particular, this session
welcomes contributions toward both the development of new machine learning
methods and the improvement of already available tools suited for big data
analysis. We also encourage the submission of new theoretical results in
the Statistical Learning Theory framework and innovative solutions to real
world problems.
In particular, topics of interest include, but are not limited to:
- Statistical Learning Theory for Large Datasets;
- Big Data Technologies;
- Learning on data Streams;
- Deep Learning for Large Datasets;
- Scalable Machine Learning for Structured Data;
- Scalable Kernel Methods for Large Datasets;
- Recommender Systems for Large Datasets;
- Big Data for Smart Cities and Transportation;
- Big Social Data Analysis;
- Big Data for Cybersecurity;
- Big Data in Bioinformatics and Healthcare;
- Big Data in the Internet of Things.

SUBMISSION:
Prospective authors must submit their paper through the IJCNN portal
following the instructions provided inhttp://www.ijcnn.org/paper-submission.
Each paper will undergo a peer reviewing process for its acceptance.

IMPORTANT DATES:
Paper submission deadline : 15 November 2016
Notification of acceptance : 20 January 2017
Camera-ready submission: 20 February 2017
The IJCNN 2017 conference : 14-19 May 2017

SPECIAL SESSION ORGANISERS
Luca Oneto <luca.oneto at unige.it> University of Genoa (Italy)
Nicolò Navarin <nnavarin at math.unipd.it> University of Padua (Italy)
Michele Donini <michele.dononi at iit.it> Istituto Italiano di Tecnologia
(Italy)
Fabio Aiolli <aiolli at math.unipd.it> University of Padua (Italy)
Davide Anguita <davide.anguita at unige.it> University of Genoa (Italy)

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Luca Oneto, PhD                            University of Genoa
web: www.lucaoneto.com               DIBRIS Department
e-mail: Luca.Oneto at unige.it          SmartLab Laboratory
e-mail: Luca.Oneto at gmail.com     Via Opera Pia 11a
Fax: +39-010-3532897                   16145 Genoa ITALY
Phone: +39-010-3532192               www.smartlab.ws
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