The methodologies on multimedia analysis usually combine different sources of information such as text, audio, and images to solve a variety of practical tasks related to advertisement, education, art, and so on. In recent years, machine learning has gained much popularity and has been intensively applied to deal with various multimedia problems. However, massive problems still remain unsolved on both algorithm design and multimedia applications.

This special issue is devoted to the publication of high quality papers on technical developments and practical applications around learning-based multimedia analyses and applications. The works on new algorithms, theories, and related applications are encouraged, and the literature reviews/surveys are also welcomed. This special issue will provide a stage for recent advances in the fields of multimedia representation, modeling, analysis, mining, retrieval, and so on.

Potential topics include but are not limited to the following:

• Novel deep neural networks for multimodal/multiview data analysis
• Sparse representation and coding for information integration and organization
• Manifold learning, subspace learning, and dimensionality reduction for social image analysis
• Optimization in multimedia computing
• Multimedia applications such as recommendation, retrieval, and social network
• Video/audio representation and analysis