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ICCIDS 2017 International Conference on Computational Intelligence in Data Science June 2 & 3,2017 Organized by Department of Computer Science and Engineering SSN College of Engineering Rajiv Gandhi Salai (OMR) Kalavakkam – 603110. Chennai, Tamilnadu, India.

CALL FOR PAPER

We invite high-quality submissions describing original and unpublished work for the conference. Accepted submissions will be included in the IEEE Xplore Digital Library.

All submissions will be subject to plagiarism check. Papers submitted for consideration should not have been published elsewhere and should not be under review or submitted for review elsewhere during the duration of consideration. At least one author of an accepted paper must register for the conference and present the paper in the conference. Only the presented papers will be included in the proceedings.

Papers that do not make the grade for publication, yet show promise, may be selected for poster presentation instead. If you are specifically interested in submitting a poster, then please ensure that the paper does not exceed 4 pages (including figures, references and appendices).

Topics of Interest

The theme of this conference is use of Computational Intelligence in Big Data. The papers need not be based only on this theme. Topics of interest for the conference include, but are not restricted to:

Topics

Foundations

Probabilistic and statistical models and theories

Machine Learning algorithms for high-velocity streaming data

Scalable analysis and learning

Data pre-processing, sampling and reduction

High dimensional data, feature selection and feature transformation

High performance computing for data analytics

Architecture, management and process for data science

Data analytics, machine learning and knowledge discovery

Knowledge discovery theories, models and systems

Learning for streaming data

Intent and insight learning

Cross-media data analytics

Big data visualization, modeling and analytics

Multimedia/stream/text/visual analytics

Computational Intelligence and Big Data Analytics

Computational theories for big data analysis

Incremental learning – theory, algorithms and applications in big data

Sparse data, feature selection, feature transformation – theory, algorithms and applications for big data

Associative memories

Probabilistic and information-theoretic methods

Supervised, unsupervised and reinforcement learning

Support vector machines and kernel methods

Time series analysis

Algorithms and libraries - Optimization for Big Data Analytics

CONTACT US

Conference Co-Chairs, ICCIDS 2017

Department of Computer Science and Engineering

SSN College of Engineering

Old Mahabalipuram Rd, Kalavakkam, Tamil Nadu 603110

Phone: 044 2746 9700

Email: iccids@ssn.edu.in

Mobile No.:

Venkata Vara Prasad +919444480822

Suresh Jaganathan +919444753058

Balasubramanian +919444574970

Jansi Rani +919176620011
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