Michael Ng

Chair Professor
(Department of Mathematics,
The University of Hong Kong)


Low Rank Tensor Completion and its Applications


In this talk, we study low rank tensor completion problems, and discuss how to use framelet, dictionary coding, deep plug-and-play prior, multiple features, total-variation approaches to solving the problem. Both theoretical and numerical results are presented to illustrate the proposed methods.


Michael K. Ng is the Director of Research Division for Mathematical and Statistical Science, Director of HKU-TCL for Joint Research Center in Artificial Intelligence, and Chair Professor of Department of Mathematics, the University of Hong Kong. His research areas are machine learning, data science, and scientific computing. https://hkumath.hku.hk/~mng/

Nicola Pancotti

Quantum research scientist
(Amazon Web Services)


Quantum Mechanics, Tensor Networks and Machine Learning


Nicola Pancotti received his Master of Science degree from the University La Sapienza, Rome, in 2014, and is currently working towards the completion of his Ph.D. at the Technical University of Munich and the Max Planck Institute of Quantum Optics in Garching, Germany. His research interests cover the dynamics of quantum systems, tensor network methods and quantum machine learning. https://de.linkedin.com/in/nicola-pancotti-19052470