56 citations · 99 across the 17 of their papers we have counts for
4 papers · 1 filter
A compressive multi-kernel method for privacy-preserving machine learning
Thee Chanyaswad, J. Morris Chang, S. Y. Kung
As the analytic tools become more powerful, and more data are generated on a daily basis, the issue of data privacy arises. This leads to the study of the design of privacy-preserv…
A Feature-map Discriminant Perspective for Pruning Deep Neural Networks
Zejiang Hou, Sun-Yuan Kung
Network pruning has become the de facto tool to accelerate deep neural networks for mobile and edge applications. Recently, feature-map discriminant based channel pruning has shown…
Scalable Kernel Learning via the Discriminant Information
Mert Al, Zejiang Hou, Sun-Yuan Kung
Kernel approximation methods create explicit, low-dimensional kernel feature maps to deal with the high computational and memory complexity of standard techniques. This work studie…
Supervising Nyström Methods via Negative Margin Support Vector Selection
Mert Al, Thee Chanyaswad, Sun-Yuan Kung
The Nyström methods have been popular techniques for scalable kernel based learning. They approximate explicit, low-dimensional feature mappings for kernel functions from the pairw…