Abstract— This paper presents a new hierarchical segmentation of the observed driving behavioral data based on the levels of abstraction of the underlying dynamics. By synthesizi...
Ato Nakano, Hiroyuki Okuda, Tatsuya Suzuki, Shinki...
This paper presents a novel metric-based framework for the task of automatic taxonomy induction. The framework incrementally clusters terms based on ontology metric, a score indic...
Abstract— Many applications require teams of robots to cooperatively execute complex tasks. Among these domains are those where successful coordination solutions must respect con...
Edward Gil Jones, M. Bernardine Dias, Anthony Sten...
Abstract. Hierarchical clustering has been proved an effective means for physically organizing large fact tables since it reduces significantly the I/O cost during ad hoc OLAP quer...
Nikos Karayannidis, Timos K. Sellis, Yannis Kouvar...
Abstract—In this paper we focus on optimizing the performance in a cluster of Simultaneous Multithreading (SMT) processors connected with a commodity interconnect (e.g. Gbit Ethe...
Georgios I. Goumas, Nikos Anastopoulos, Nectarios ...