Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
When viewing images on a monitor, we are adapted to the lighting conditions of our viewing environment as well as the monitor itself, which can be very different from the lighting ...
The idea of learning overcomplete dictionaries based on the paradigm of compressive sensing has found numerous applications, among which image denoising is considered one of the m...
—In this work we address the problem of state estimation in dynamical systems using recent developments in compressive sensing and sparse approximation. We formulate the traditio...
Adam Charles, Muhammad Salman Asif, Justin K. Romb...
Significant power savings can be achieved on voltage/frequency configurable platforms by dynamically adapting the frequency and voltage according to the workload (complexity). Vid...