Abstract. Algorithms dealing with massive data sets are usually designed for I/O-efficiency, often captured by the I/O model by Aggarwal and Vitter. Another aspect of dealing with ...
Abstract—Dynamically allocated and manipulated data structures cannot be translated into hardware unless there is an upper bound on the amount of memory the program uses during a...
Byron Cook, Ashutosh Gupta, Stephen Magill, Andrey...
Abstract. With the drastic increase of object trajectory data, the analysis and exploration of trajectories has become a major research focus with many applications. In particular,...
Abstract. We study online scheduling to minimize flow time plus energy usage in the dynamic speed scaling model. We devise new speed scaling functions that depend on the number of ...
Tak Wah Lam, Lap-Kei Lee, Isaac Kar-Keung To, Prud...
Abstract a paradigm of modern Machine Learning (ML) which uses rewards and punishments to guide the learning process. One of the central ideas of RL is learning by “direct-online...