Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...
A virtual cluster is a promising technology for reducing management costs and improving capacity utilization in datacenters and computer centers. However, recent cluster virtualiz...
In this paper we study the structural evolution of the AS topology as inferred from two different datasets over a period of seven years. We use a variety of topological metrics to...
Hamed Haddadi, Damien Fay, Steve Uhlig, Andrew W. ...
High dimensional data has always been a challenge for clustering algorithms because of the inherent sparsity of the points. Recent research results indicate that in high dimension...
In this paper, we explore experimentally the use of the commute time of the continuous-time quantum walk for graph drawing. For the classical random walk, the commute time has bee...