We propose a new algorithm for Approximate Joint Diagonalization (AJD) with two main advantages over existing state-of-the-art algorithms: Improved overall running speed, especial...
Abstract. We present fully polynomial approximation schemes for the problem of minimizing completion time variance of a set of n jobs on a single machine. The fastest of these sche...
Wieslaw Kubiak, Jinliang Cheng, Mikhail Y. Kovalyo...
We present a fast algorithm for computing approximate quantiles in high speed data streams with deterministic error bounds. For data streams of size N where N is unknown in advanc...
We present algorithms for fast quantile and frequency estimation in large data streams using graphics processor units (GPUs). We exploit the high computational power and memory ba...
Naga K. Govindaraju, Nikunj Raghuvanshi, Dinesh Ma...
This paper shows how to construct static analyzers using tree automata and rewriting techniques. Starting from a term rewriting system representing the operational semantics of the...
Yohan Boichut, Thomas Genet, Thomas P. Jensen, Luk...