活动简介

ICMLA 2017 aims to bring together researchers and practitioners to present their latest achievements and innovations in the area of machine learning (ML). The conference provides a leading international forum for the dissemination of original research in ML, with emphasis on applications as well as novel algorithms and systems. Following the success of previous ICMLA conferences, the conference aims to attract researchers and application developers from a wide range of ML related areas, and the recent emergence of Big Data processing brings an urgent need for machine learning to address these new challenges. The conference will cover both machine learning theoretical research and its applications. Contributions describing machine learning techniques applied to real-world problems and interdisciplinary research involving machine learning, in fields like medicine, biology, industry, manufacturing, security, education, virtual environments, games, are especially encouraged.

征稿信息

重要日期

2017-07-06
初稿截稿日期
2017-09-09
初稿录用日期
2017-10-01
终稿截稿日期

TOPICS OF INTEREST

  1. Statistical Learning
  2. Neural Network Learning
  3. Learning Through Fuzzy Logic
  4. Learning Through Evolution
  5. Reinforcement Learning
  6. Multi-strategy Learning
  7. Cooperative Learning
  8. Planning and Learning
  9. Multi-agent Learning
  10. Online and Incremental Learning
  11. Scalability of Learning Algorithms
  12. Inductive Learning
  13. Inductive Logic Programming
  14. Bayesian Networks
  15. Support Vector Machines
  16. Case-based Reasoning
  17. Grammatical Inference
  18. Knowledge Acquisition and Learning
  19. Knowledge Discovery in Databases
  20. Knowledge Intensive Learning
  21. Knowledge Representation and Reasoning
  22. Machine Learning for Information Retrieval
  23. Learning Through Mobile Data Mining
  24. Machine Learning for Web Navigation and Mining
  25. Text and Multimedia Mining
  26. Feature Extraction and Classification
  27. Distributed and Parallel Learning Algorithms and Applications
  28. Computational Learning Theory
  29. Theories and Models for Plausible Reasoning
  30. Computational Learning Theory
  31. Cognitive Modeling
  32. Hybrid Learning Algorithms
  33. Multi-lingual knowledge acquisition and representation
  34. Applications of Machine learning in:
  • Medicine and health informatics
  • Bioinformatics and systems biology
  • Industrial and engineering applications
  • Security
  • Smart cities
  • Game playing and problem solving
  • Intelligent virtual environments
  • Economics, business and forecasting
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

    12月18日

    2017

    12月21日

    2017

  • 07月06日 2017

    初稿截稿日期

  • 09月09日 2017

    初稿录用通知日期

  • 10月01日 2017

    终稿截稿日期

  • 12月21日 2017

    注册截止日期

主办单位
IEEE
联系方式
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