Abstract. We propose a popularity weighted ranking algorithm for academic digital libraries that uses the popularity factor of a publication venue overcoming the limitations of imp...
Instance-based learning algorithms are widely used due to their capacity to approximate complex target functions; however, the performance of this kind of algorithms degrades signi...
—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
The vast majority of visualization tools introduced so far are specialized pieces of software that are explicitly run on a particular dataset at a particular time for a particular...
Eamonn J. Keogh, Li Wei, Xiaopeng Xi, Stefano Lona...
In this paper we present a sublinear time (1+ )-approximation randomized algorithm to estimate the weight of the minimum spanning tree of an n-point metric space. The running time...