活动简介

The conference provides an opportunity for the researchers, engineers, developers and practitioners from academia and industry to discuss and address the solicit experimental, theoretical work and methods in solving problems and to share their experience, exchange and cross-fertilize their ideas in the fields of Data Science and Computational Intelligence. This conference will be useful for professionals working in data science, big data, machine learning, artificial intelligence and predictive modeling.

We invite high-quality submissions describing original and unpublished work for the conference.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).

征稿信息

重要日期

2017-02-01
摘要截稿日期
2017-04-10
初稿截稿日期
2017-05-11
初稿录用日期
2017-05-20
终稿截稿日期

征稿范围

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

留言
验证码 看不清楚,更换一张
全部留言
重要日期
  • 会议日期

    06月02日

    2017

    06月03日

    2017

  • 02月01日 2017

    摘要截稿日期

  • 04月10日 2017

    初稿截稿日期

  • 05月11日 2017

    初稿录用通知日期

  • 05月20日 2017

    终稿截稿日期

  • 06月03日 2017

    注册截止日期

主办单位
IEEE
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询