Routing algorithms are traditionally evaluated under Poisson-like traffic distributions. This type of traffic is smooth over large time intervals and has been shown not necessaril...
Time series are a data type of utmost importance in many domains such as business management and service monitoring. We address the problem of visualizing large time-related data ...
Ming C. Hao, Umeshwar Dayal, Daniel A. Keim, Tobia...
In this study Principal Component Analysis (PCA), Non-negative Matrix Factorization (NMF) and Nonnegative Tensor Factorization (NTF) are applied as dimension reduction methods in ...
Alexey Andriyashin, Jussi Parkkinen, Timo Jaaskela...
Terascale simulations produce data that is vast in spatial, temporal, and variable domains, creating a formidable challenge for subsequent analysis. Feature extraction as a data r...
Dimensionality reduction is an important preprocessing step in high-dimensional data analysis without losing intrinsic information. The problem of semi-supervised nonlinear dimensi...