We present an overview of our ongoing work on parallelizing self-adjusting-computation techniques. In self-adjusting computation, programs can respond to changes to their data (e....
Matthew Hammer, Umut A. Acar, Mohan Rajagopalan, A...
This paper presents an overview of pARMS, a package for solving sparse linear systems on parallel platforms. Preconditioners constitute the most important ingredient in the solutio...
We present a new Coprime Blurred Pair (CBP) theory that may benefit a number of computer vision applications. A CBP is constructed by blurring the same latent image with two unkn...
Data cloning method is a new computational tool for computing maximum likelihood estimates in complex statistical models such as mixed models. This method is synthesized with inte...
The Ensemble methodology supports the design and implementation of message passing applications, particularly MPMD and those demanding irregular or partially regular process topol...