Capacity scaling is a hierarchical approach to graph representation that can improve theoretical complexity and practical efficiency of max-flow/min-cut algorithms. Introduced by ...
Recently, advances have been made in continuous, normal– distribution–based Estimation–of–Distribution Algorithms (EDAs) by scaling the variance up from the maximum–like...
Learning to cope with domain change has been known
as a challenging problem in many real-world applications.
This paper proposes a novel and efficient approach, named
domain ada...
Yu-Gang Jiang, Jun Wang, Shih-Fu Chang, Chong-Wah ...
Abstract— The effectiveness of service provisioning in largescale networks is highly dependent on the number and location of service facilities deployed at various hosts. The cla...
This paper presents a middleware framework for storing, accessing and analyzing massive-scale semantic graphs. The framework, MSSG, targets scale-free semantic graphs with O(1012 ...