Time series are an important type of data with applications in virtually every aspect of the real world. Often a large number of time series have to be monitored and analyzed in p...
Ming C. Hao, Umeshwar Dayal, Daniel A. Keim, Tobia...
The standard framework of machine learning problems assumes that the available data is independent and identically distributed (i.i.d.). However, in some applications such as image...
We present a study of the prosody – seen in a broader sense – that supports the theory of the interrelationship function of speech. “Pure emotions” are meant to show a rela...
Modeling and estimation of switching activities remain to be important problems in low-power design and fault analysis. A probabilistic Bayesian Network based switching model can ...
We investigate the relationship between two kinds of vertex colorings of graphs: uniquemaximum colorings and conflict-free colorings. In a unique-maximum coloring, the colors are ...