In this paper we propose a new packet classification algorithm, which can substantially improve the performance of a classifier by decreasing the rulebase lookup latency. The algor...
Lynn Choi, Jaesung Heo, Hyogon Kim, Jinoo Joung, S...
Efficiently rendering highly structured models distant from the viewer constitutes a difficult task since the geometric complexity has to be reduced extremely while simultaneously...
In this paper we introduce an efficient implementation of asynchronously parallel genetic algorithm with adaptive genetic operators. The classic genetic algorithm paradigm is exte...
In this paper we present a novel framework for evolving ART-based classification models, which we refer to as MOME-ART. The new training framework aims to evolve populations of ART...
Rong Li, Timothy R. Mersch, Oriana X. Wen, Assem K...
Abstract--Limited preemption scheduling has been introduced as a viable alternative to non-preemptive and fullypreemptive scheduling when reduced blocking times need to coexist wit...
Marko Bertogna, Giorgio C. Buttazzo, Mauro Marinon...