23 citations · 27 across the 5 of their papers we have counts for
5 papers
Privacy Enhancing Machine Learning via Removal of Unwanted Dependencies
Mert Al, Semih Yagli, Sun-Yuan Kung
The rapid rise of IoT and Big Data has facilitated copious data driven applications to enhance our quality of life. However, the omnipresent and all-encompassing nature of the data…
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…
On the Capacity of the Peak Power Constrained Vector Gaussian Channel: An Estimation Theoretic Perspective
Alex Dytso, Mert Al, H. Vincent Poor +1
This paper studies the capacity of an -dimensional vector Gaussian noise channel subject to the constraint that an input must lie in the ball of radius centered at the origi…
Ratio Utility and Cost Analysis for Privacy Preserving Subspace Projection
Mert Al, Shibiao Wan, Sun-Yuan Kung
With a rapidly increasing number of devices connected to the internet, big data has been applied to various domains of human life. Nevertheless, it has also opened new venues for b…