The 4th International Workshop on Machine Learning on Multimedia and Applications (MLMA 2026)

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 2025) 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, and set future directions in in all aspects of machine learning and technologies on multimedia applications.

Organization Committee
Program Committee Co-chairs

• Yi-Cheng Chen, National Central University, Taiwan

• Yan Liu, Hong Kong Polytechnic University, Hong Kong

• Lin Hui, Tamkang University, Taiwan

• Sheng-Chih Chen, National ChengChi University, Taiwan

Program Committee Members

• Philip S. Yu, University of Illinois at Chicago, USA

• Jiannong Cao, Hong Kong Polytechnic University, Hong Kong

• Vincent S. Tseng, National Chiao Tung University, Taiwan

• Keith Chan, Hong Kong Polytechnic University, Hong Kong

• Joshua Zhexue Huang, Shenzhen University, China

• Yan Huang, University of North Texas, USA

• Wang-Chien Lee, Pennsylvania State University, USA

• Xiaohua Tony Hu, Drexel University, USA

• Wei-Shinn Ku, Auburn University, USA

• Xiang Zhang, Case Western Reserve University, USA

• Dai Bing Tian, Singapore Management University, Singapore

• Meng-Fen Chiang, Singapore Management University, Singapore

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 technology work 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

• Authors are invited to submit their original research that has not previously been submitted or published at any other venue.

• All papers must follow the Springer LNCS/CCIS template, NOT longer than 6 pages

• Template: Word : LaTeX

Workshop proceedings will be included and indexed in the Communications in Computer and Information Science (CCIS)

Submission & Format information: https://easychair.org/conferences?conf=mlma2026

Workshop Contact Person

Yi-Cheng Chen, National Central University, Taiwan
Email: ycchen@mgt.ncu.edu.tw