Toronto Workshop on Graph Spectral Machine Learning 2021

August 23, 2021


  1. 9:00 - 9:10 Opening Remarks

  2. 9:10 - 9:40: Self-supervised graph-based machine learning for point cloud analysis (Wei's group)

  3. 9:40 - 10:10 Learning Sparse Graph Laplacian with K Eigenvector Prior via Iterative GLASSO and Projection (Gene's group)

  4. 10:10 - 10:40 Gershgorin Disc Perfect Alignment for Metric and Classifier Learning (Gene's group)

  5. 10:40 - 11:10 Open Discussion: Graph-based Machine Learning

  6. 11:10 - 11:20 Break

  7. 11:20 - 11:50 CausalTT: Causal Discovery by Tensor Transformer from Videos (Xiao-Ping's group)

  8. 11:50 - 12:20 VPCC compression artifacts removal (Zhu's group)

  9. 12:20 - 12:50 Open Discussion: Machine Learning for MM Processing / Analysis

  10. 12:50 - 13:00 Closing Remarks


  • Prof. Gene Cheung (York University)
  • Prof. Wei Hu (PKU)
  • Prof. Xiao-Ping Zhang (Ryerson University)
  • Prof. Zhu Li (Missouri)

Toronto Workshop on Graph Spectral Machine Learning 2020

August 19, 2020


  1. 10:00AM to 10:10AM
  2. Welcome remarks

  3. 10:10AM to 10:55AM
    Dynamic Tensor-based Spatiotemporal Graph Neural Network with COVID-19 Applications
    Chengcheng Jia (Postdoc, Ryerson)
    Slide: PDF

  4. 10:55AM to 11:40AM
    On the basics of graph convolutional networks (GCNs), their several existing architectures and potential applications
    Tohid Yousefi Rezaii (Postdoc, Ryerson)
    Slide: PDF

  5. 11:40AM to 12:25PM
    Signed Graph Metric Learning via Gershgorin Disc Alignment
    Gene Cheung (Associate professor, York University)
    Slide: PDF

  6. 12:25PM to 1:10PM
    Sampling of 3D Point Cloud via Gershgorin Disc Alignment
    Chinthaka Dinesh (Graduate student, Simon Fraser University)
    Slide: PDF


The First Toronto Workshop on Graph Spectral Machine Learning

Ryerson University August 22, 2019

List of presentations:

  1. Title: Fast Graph Sampling using Gershgorin Disc Alignment
    Speaker: Gene Cheung (Associate Professor, York University)
    Slide: PDF

  2. Title: Graph Sampling for Matrix Completion
    Speaker : Fen Wang (PhD student, Xidian University)
    Slide: PDF

  3. Title: Feature Graph Learning for 3D Point Cloud Denoising
    Speaker : Wei Hu (Assistant Professor, Peking University)
    Slide: PDF
  1. Title: Applications of Graph Signal Processing in Functional Brain Networks
    Speaker: MohammadReza Ebrahimi (University of Toronto)
    Slide: The work is still in progress

  2. Title: Time series and spatio-temporal forecasting problem as a data imputation problem
    Speaker: Tuan Tran (Ryerson University)
    Slide: PDF


  • Prof. Gene Cheung (York University)
  • Prof. Xiao-Ping Zhang (Ryerson University)
  • Prof. Ashish Khisti (University of Toronto)