Approximate arithmetic is a promising, new approach to lowenergy designs while tackling reliability issues. We present a method to optimally distribute a given energy budget among...
Zvi M. Kedem, Vincent John Mooney, Kirthi Krishna ...
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Using the subband technique, an LTI system can be implemented by the composition of an analysis filterbank, followed by a transfer matrix (subband model) and a synthesis filterbank...
There has been much recent work on measuring image statistics and on learning probability distributions on images. We observe that the mapping from images to statistics is many-to...
A novel framework for providing probabilistically-bounded approximate answers to non-holistic aggregate range queries in OLAP is presented in this paper. Such a framework allows u...