Theme  of   the   Workshop

Recently, machine learning is affecting the lives of people from moment to moment. This techniques have been proven and widely used in several domains. Multimedia has emerged as one key area for the application of machine learning techniques, which involves special considerations the data is typically of very high dimension. Due to the widespread practicability, there are several important aspects to apply various machine learning on multimedia, such as over-¬fitting/under-¬fitting, regularization, interpretability, supervised/unsupervised methods, and handling of missing data. The 1st International Workshop on Machine Learning on Multimedia Applications (MLMA 2018) will serve as a forum for researchers and technologists to discuss the state-of-the-art, exchange their experiences, present their contributions and original ideas including learning models and applications, and set future directions in in all aspects of machine learning and technologies on multimedia.

Workshop Scope

The topics of interest related to this workshop include, but are not limited to:

  • Learning algorithm on multimedia
    - Unsupervised learning
    - Supervised learning
  • Dimensionality reduction
    - Principal Component Analysis
    - Independent Component Analysis
    - Self-Organizing Maps
    - Multi-Dimensional Scaling
  • Deep learning technologywork structure
    - Model optimization
    - Learning rate tuning
  • Data processing
    - Data Collection
    - Data Cleaning
    - Big data
  • Problem on implementation
  • Applications
    - Social Network, Recommendation System
    - Mobility, Sensor Network
    - Bioinformatics
    - E-Commerce
  • Paper Submission

  • Papers submitted must be formatted in PDF files, IEEE Computer Society Press Format, NOT longer than 6 pages
  • Workshop proceedings will be included and indexed in the IEEE Digital Libraries (EI)
  • Submission & Format information: