Machine Learning Designs, Implementations and Techniques

Submission Deadline: 15 February 2020 IEEE Access invites manuscript submissions in the area of Machine Learning Designs, Implementations and Techniques. Most modern machine learning research is devoted to improving the accuracy of prediction. However, less attention is paid to deployment of machine and deep learning systems, supervised /unsupervised techniques for mining healthcare data, and time series similarity and irregular temporal data analysis. Most deployments are in the cloud, with abundant and scalable resources, and a free choice of computation platform. However, with the advent of intelligent physical devices—such as intelligent robots or self-driven cars—the resources are more limited, and the latency may be strictly bounded. To address these questions, the focus of this Special Section in IEEE Access is on machine and deep learning designs, implementations and techniques, including both system level topics and other research questions related to the general use and framework of machine learning algorithms. The topics of interest include, but are not limited to:
  • Real time implementation of machine and deep learning,
  • System level implementation, considering full pipeline from raw data until the decision layer
  • Novel and innovative applications with strong emphasis on design and implementation
  • Novel approaches for Temporal / Spatial/Spatio-Temporal Association analysis
  • Pattern discovery from Time stamped Temporal and Interval databases
  • High performance data mining in cloud
  • Novel approaches for handling Uncertain and Imbalanced data
  • Supervised/Unsupervised techniques for mining healthcare data
  • Deep learning for translational bio-informatics
  • Periodic/Sequential pattern mining
  • Evolutionary algorithms
  • Privacy-Preserving Data mining
  • Time series similarity and Irregular temporal data analysis
  • Mining Text Web and Social network data
  • Imputation techniques for Temporal data
  • Causality and Event Processing
  • Applications of Data Mining in Anomaly and Intrusion detection
  • Applications to medical informatics
  We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.   Associate Editor:  Shadi A. Aljawarneh, Jordan University of Science and Technology, Jordan Guest Editors:
    1. Oguz Bayat, Altinbas University, Turkey
    2. Juan A. Lara, Madrid Open University, Udima, Spain
    3. Robert P. Schumaker, University of Texas at Tyler, USA
  Relevant IEEE Access Special Sections:
  1. Visual Analysis for CPS Data
  2. Emerging Approaches to Cyber Security
  3. Data-Enabled Intelligence for Digital Health
IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide Article submission: Contact Associate Editor and submit manuscript to: For inquiries regarding this Special Section, please contact:,