3 papers
cs.LG2019
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…
cs.LG2018
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…
cs.IT2018
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…