[CFP][INNS-BDDL 2018] Extension of paper submission deadline to 15th February 2018

[INNS-BDDL 2018 - Indonesia]

Apologies for cross postings.

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CALL FOR PAPERS

The 3rd INNS Conference on Big Data and Deep Learning 2018

April 17-19, 2018, Bali, Indonesia

Homepage: http://www.innsbigdata2018.org

#######################Description:######################

The International Neural Network Society (INNS) is the premiere organization for
individuals interested in a theoretical and computational understanding of the
brain and applying that knowledge to develop new and more effective forms of
machine intelligence. INNS was formed in 1987 by the leading scientists in the
neural network field.

Researchers and colleagues who work in the area of big data and machine
learning, we are happy to announce "The 3 rd INNS Conference on Big Data and
Deep Learning 2018 (INNS BDDL 2018) will be held on April 18 b 19, 2018 in Sanur
b Bali, Indonesia. The aim of this conference is to create a valuable and
important forum for scientists and engineers throughout the world to present the
latest research findings and idea at the forefront of Big Data and Deep
Learning.

Accepted papers will be published in the Procedia Computer Science by Elsevier, which is indexed by Scopus.
Several papers will be selected for possible publication in top journals.
A preliminary list of such journals includes:
- Cognitive Systems Research (Scopus SJR 0.648, Impact Factor 1.182)
- Cognitive Computation (Scopus SJR 0.823, Impact Factor 3.441)
- Big Data Analytics
- Evolving Systems (Scopus SJR 0.459, Impact Factor 1.067)
- International Journal of Neural Systems (Scopus SJR 1.121, Impact Factor 6.333)
- and possibly others

The conference will feature a comprehensive technical program with technical tracks on:
Track 1: Big Data
Track 2: Big Data Algorithms
Track 3: Deep Learning
Track 4: Application Areas

Important Dates
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* Deadline of full paper submission 15 February 2018
* Decision notification 15 March 2018
* Conference 17 - 19 April 2018
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Previous INNS Conference:
INNS 2016 in Thessaloniki, Greece
INNS 2015 in San Francisco, USA

#################### Organizing committees ###############
General chairs
Seiichi Ozawa, Kobe University, Japan
Ah-Hwee Tan, Nanyang Technological University, Singapore

Program Chairs
Plamen P. Angelov, Lancaster University, UK
Asim Roy, Arizona State University, USA
Mahardhika Pratama, Nanyang Technological University, Singapore

Local Committee Chairs
Dieky Adzkiya, Institut Teknologi Sepuluh Nopember, Indonesia

Advisory Board
Yew-Soon Ong, Nanyang Technological University, Singapore
Robert Kozma, University of Memphis, USA
Sankar K. Pal, Indian Statistical Institute, India
Haibo He, University of Rhode Island, USA
Witold Pedrycz, University of Alberta, Alberta, Canada
Leszek Rutkowski, Czestochowa University of Technology, Poland
Nikola Kasabov, Auckland University of Technology, New Zealand
Fernando Gomide, University of Campinas, Brazil
Marley Vellasco, PontifC-cia Universidade CatC3lica do Rio de Janeiro, Brazil
Yoonsuck Choe, Texas A&M University
Minho Lee, Kyungpook National University, South Korea
Bao-Liang Lu, Shanghai Jiao Tong University, China
Irwin King, the Chinese University of Hong Kong, Hong kong
Mohammad Nuh, Institut Teknologi Sepuluh Nopember, Indonesia
Joni Hermana, Institut Teknologi Sepuluh Nopember, Indonesia
Heru Setyawan, Institut Teknologi Sepuluh Nopember, Indonesia

Tutorials/Workshop Chairs
Igor Skrjanc, University of Ljubljana, Slovenia
Sundaram Suresh, Nanyang Technological University, Singapore

Poster Sessions Chairs
Eko Setiadji, Institut Teknologi Sepuluh Nopember, Indonesia
Agus Salim, La Trobe University, Australia

Special Sessions Chairs
Justin Wang, La Trobe University, Australia
Yongping Pan, National University of Singapore, Singapore

Panel Chairs
Sreenatha Anavatti, University of New South Wales, Australia
Mukesh Prasad, University of Technology, Sydney, Australia
Achmad Affandi, Institut Teknologi Sepuluh Nopember, Indonesia

Awards Chairs
Tapabrata Ray, University of New South Wales, Australia
Dejan Dovzan, University of Ljubljana, Slovenia
Richard J. Oentaryo, McLaren Applied Technologies, Singapore

Publication Chairs
Edwin Lughofer, Johannes Kepler University, Austria
Jose Antonio Iglesias, Carlos III University of Madrid, Spain
Moamar Sayed?Mouchaweh, Institute Mines Telecom Lille Douai, France

Publicity Chair
Simone Scardapane, Sapienza University, Italy
Teng Teck Hou, Singapore Management University, Singapore
Hendro Nurhadi, Institut Teknologi Sepuluh Nopember, Indonesia

International Liaison Chairs
Yun Sing Koh, University of Auckland, New Zealand
Deepak Puthal, University of Technology Sydney, Australia
Wirawan, Institut Teknologi Sepuluh Nopember, Indonesia

Webmaster
Mohamad Abdul Hady, Institut Teknologi Sepuluh Nopember, Indonesia
Andri Ashfahani, Institut Teknologi Sepuluh Nopember, Indonesia
Choiru Zab in, La Trobe University, Australia


###### Topics and Areas include, but not limited to the following######
==BIG DATA
Autonomous, online, incremental learning in big data
High dimensional data, feature selection, feature transformation for big data
Scalable algorithms for big data
Big data analytics
Data stream analytics
Parallel & distributed computing for big data analytics (cloud, map-reduce, etc.)
Online learning
Online multimedia/stream/text analytics
Link and graph mining
Big data and cloud computing, large scale stream processing on the cloud
Big data and collective intelligence/collaborative learning
Big data and hybrid systems
Big data and self-aware systems
Big data and infrastructure
Big data visualization

==Big Data Algorithm
Neuromorphic hardware for scalable machine learning
Evolving systems for big data analytics
Evolutionary systems and big data
Fuzzy systems and big data
Cognitive modelling and big data
Probabilistic approach for big data
Concept drift detection for big data
Granular computing for big data
Transfer learning for big data

==Deep Learning
Deep belief network
Convolutional neural network
Long short term memory
Deep network architecture
Deep autoencoder
Deep stacked network
Deep learning for natural language processing
Deep learning for machine vision
Evolving deep network
Transfer learning in deep learning
Online deep learning

==Application Areas
Banking and Securities
Communications, Media and Entertainment
Healthcare Providers
Education
Manufacturing & Natural Resources
Government
Insurances
Retail & Wholesale Trade
Transportation
Energy & Utilities, Etc.

##########################Sponsoring Organizations##########################
* INNS - International Neural Network Society
* PUI-PT MIA-RC ITS - Mechatronics and Industrial Automations - Research Center, Institut Teknologi Sepuluh Nopember, Indonesia
* Elsevier
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