INNS-BDDL 2018

INNS-BDDL 2018
INNS-BDDL 2018 : The 3rd INNS Conference on Big Data and Deep Learning 2018
Dates	2018/04/17 (iCal) - 2018/04/19
Homepage:	http://www.innsbigdata2018.org
Location
Location:	Bali, Indonesia
Loading map... {"minzoom":false,"maxzoom":false,"mappingservice":"leaflet","width":"280px","height":"280px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"wmsoverlay":false,"copycoords":false,"static":false,"zoom":false,"defzoom":14,"layers":["OpenStreetMap"],"overlaylayers":[],"resizable":false,"enablefullscreen":false,"scrollwheelzoom":true,"markercluster":false,"clustermaxzoom":20,"clusterzoomonclick":true,"clustermaxradius":80,"clusterspiderfy":true,"geojson":"","locations":[{"text":"\u003Cb\u003E\u003Cdiv class=\"mw-parser-output\"\u003E\u003C/div\u003E\u003C/b\u003E\u003Chr /\u003E\u003Cdiv class=\"mw-parser-output\"\u003E\u003C/div\u003E","title":"","link":"","lat":-8.2271303,"lon":115.1919203,"icon":""}],"imageoverlays":null}
Important dates
Submissions:	2017/11/02
Table of Contents

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

1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 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

Previous INNS Conference: INNS 2016 in Thessaloniki, Greece INNS 2015 in San Francisco, USA

1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 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

1. 1. 1. 1. 1. 1. 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.

1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. Sponsoring Organizations##########################

• INNS - International Neural Network Society
• MTC - Mechatronic Technology Center, Institut Tecknologi Sepuluh Nopember