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...
—This paper explores the use of compiler optimizations which optimize the layout of instructions in memory. The target is to enable the code to make better use of the underlying ...
Monitoring of environmental phenomena with embedded networked sensing confronts the challenges of both unpredictable variability in the spatial distribution of phenomena, coupled ...
Maxim A. Batalin, Mohammad H. Rahimi, Yan Yu, Duo ...
In this paper, we propose to model the blended search problem by assuming conditional dependencies among queries, VSEs and search results. The probability distributions of this mo...
TCP Throughput Collapse, also known as Incast, is a pathological behavior of TCP that results in gross under-utilization of link capacity in certain many-to-one communication patt...
Yanpei Chen, Rean Griffith, Junda Liu, Randy H. Ka...