Many machine learning algorithms can be formulated as the minimization of a training criterion which involves (1) \training errors" on each training example and (2) some hype...
We propose a design theory that tackles dynamic complexity in the design for Information Infrastructures (IIs) defined as a shared, open, heterogeneous and evolving socio-technica...
The ratio of two probability density functions is becoming a quantity of interest these days in the machine learning and data mining communities since it can be used for various d...
Accurately evaluating statistical independence among random variables is a key element of Independent Component Analysis (ICA). In this paper, we employ a squared-loss variant of ...
Eigenvectors of data matrices play an important role in many computational problems, ranging from signal processing to machine learning and control. For instance, algorithms that ...