We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density func...
The Collect problem for an asynchronous shared-memory system has the objective for the processors to learn all values of a collection of shared registers, while minimizing the tot...
Bogdan S. Chlebus, Dariusz R. Kowalski, Alexander ...
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Mean shift clustering is a powerful unsupervised data
analysis technique which does not require prior knowledge
of the number of clusters, and does not constrain the shape
of th...
We present an algorithm for detecting human actions
based upon a single given video example of such actions.
The proposed method is unsupervised, does not require
learning, segm...