Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
Many existing spectral clustering algorithms share a conventional graph partitioning criterion: normalized cuts (NC). However, one problem with NC is that it poorly captures the g...
Abstract. A random iteration algorithm for graph-directed sets is defined and discussed. Similarly to the Barnsley-Elton’s theorem, it is shown that almost all sequences obtaine...
Given two 3-connected graphs G and H, a construction sequence constructs
G from H (e. g. from the K4) with three basic operations, called
the Barnette-Grünbaum operations. These...
We present a vision based, adaptive, decision theoretic model of human facial displays in interactions. The model is a partially observable Markov decision process, or POMDP. A POM...