Visualization for understanding and developing machine learning

NTU visualizationObjective: Develop advanced techniques and tools for visualizing different aspects of machine learning jointly in the same framework.

PIs: Anders Ynnerman (LiU), Jianmin Zheng (NTU)

Targeted problem: Visualization of the distributions of the input data with effective filters, development of new data structures for handling high dimensional and heterogeneous data and networks, and investigation of how to present and analyse the results with respect to the input data.

Approach:

  • Our approach is to supply a holistic view of a machine learning system and provide interactive visualization that facilitates human involvement and various stages of machine learning.
  • We start with deep learning and computer vision tasks as the initial application domain in the area of facial reconstruction.
  • We combine new and traditional data visualization methods and will develop a project demonstrator.