In this paper, we present an abstract framework for online approximation of time-series data that yields a unified set of algorithms for several popular models: data streams, amnes...
We introduce three new innovations for compression using LDPCs for the Slepian-Wolf problem. The first is a general iterative Slepian-Wolf decoding algorithm that incorporates the...
Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets...
This paper presents a novel framework for elliptical weighted average (EWA) surface splatting with time-varying scenes. We extend the theoretical basis of the original framework b...
Simon Heinzle, Johanna Wolf, Yoshihiro Kanamori, T...
— This paper presents a fast analytical method for estimating the throughput of pipelined asynchronous systems, and then applies that method to develop a fast solution to the pro...