[Comp-neuro] [INNS-BDDL 2018] Call for Papers

Teng Teck Hou dengdehao at gmail.com
Fri Aug 11 04:16:17 CEST 2017


[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, Sanur - 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 – 19, 2018 in
Sanur – 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 by Elsevier, Scopus indexed.

Several papers will be selected for possible publication in top journals.

 

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

###################################################################

* Tutorial and workshop proposals (Submission)               15 September
2017

* Tutorial and workshop proposals (Decision)     30 September 2017

 

* Paper submission                                                         2
November 2017

* Decision notification                                                   31
December 2017

* 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, Pontifícia Universidade Católica 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 Za’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

* MTC - Mechatronic Technology Center, Institut Tecknologi Sepuluh Nopember

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