University of Konstanz
Graduiertenkolleg / PhD Program
Computer and Information Science

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Author(s) Brandes, U., Pich, C.
Title Eigensolver methods for progressive multidimensional scaling of large data
Abstract We present a novel sampling-based approximation technique for classical multidimensional scaling that yields an extremely fast layout algorithm suitable even for very large graphs. It produces layouts that compare favorably with other methods for drawing large graphs, and it is among the fastest methods available. In addition, our approach allows for progressive computation, i.e. a rough approximation of the layout can be produced even faster, and then be refined until satisfaction.
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