2019 International Conference on Data Mining and Machine Learning

ICDMML 2019


Data Mining & Analysis



2019 International Conference on Data Mining and Machine Learning (ICDMML 2019) will be held on April 29 - 30 2019 in Hong Kong. The symposium will focus on the frontier topics in the theoretical and applied Data Mining, Machine Learning and AI subjects.
Basic Information
Paper Review
All submissions to the ICDMML will be sent to at least 2 reviewers and evaluated based on originality, technical and research content, relevance to conference, contributions, and readability. The full paper submissions will be chosen based on technical merit, interest, applicability, and how well they fit a coherent and balanced technical program.
Important Dates
Registration Deadline:
From now till 29th November 2018 (Early Bird)
30th November 2018 to 28th February 2019 (Standard)
28th February 2019 to March 29th 2019 (Late Registration)
Conference Date: April 29-30 2019
Publishing
The accepted papers will be published by Volkson Press. Some selected papers will be published in Journals.
Indexes
Volkson Press will submit the proceedings to Ei Compendex, Scopus, CNKI for indexing.
CFP link: http://www.icdmml.org/cfp.html
1 Artificial Intelligence
including the following topics but not limited to
Artificial Intelligence
Biometric Identification
Biocomputing and Bioinformatics
Computational Intelligence
Cognitive Processing
Computer Vision
Deep learining
Document Recognition and Understanding
Humanoid Robot
Intelligent Information Processing
Intelligent Modeling and Control Theory
Intelligent Vehicle
Intelligent Video Surveillance
Machine Learning
Mass Information Processing
Multimedia Information Processing
Nature Language Processing
Nonlinear System
Pattern Recognition
Quantum Computation and Quantum Information
Space Robot
Speech and Character Recognition
Signal Processing
Unmanned Aircraft
Word Recognition
2 Data Mining
including the following topics but not limited to
Abnormality and data detection
Algorithms for new, structured, data types, such as arising in chemistry, biology, environment, and other scientific domains
Big data analytic and High performance implementations of data mining algorithms
Developing a unifying theory of data mining
Distributed data mining and mining multi-agent data
Mining high speed data streams
Mining in networked settings: web, social and computer networks, and online communities
Mining sequences and sequential data
Mining sensor data
Mining spatial and temporal datasets
Mining textual and unstructured datasets
Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis)
3 Machine Learning
including the following topics but not limited to
Active learning
Computational learning theory
Distance measurement learning
Deep learning
Incremental learning and online learning
Integrated learning
Limit learning
Machine learning new theory
Manifold learning
Multi - task learning
Multi - sign learning
Reinforcement learning
Manifold learning
Semi-supervised learning
Submission link: http://www.icdmml.org/submission.html
Contact Us:
Url: www.ICDMML.org
HK Tel: +852-5607-9095
Email: ICDMML@ieti.net