We continue our study of online prediction of the labelling of a graph. We show a fundamental limitation of Laplacian-based algorithms: if the graph has a large diameter then the ...
We propose a visualization approach for large dynamic graph structures with high degree variation and low diameter. In particular, we reduce visual complexity by multiple modes of ...
Background: Analyzing differential-gene-expression data in the context of protein-interaction networks (PINs) yields information on the functional cellular status. PINs can be for...
Alexander Platzer, Paul Perco, Arno Lukas, Bernd M...
Abstract. We study online learning algorithms that predict by combining the predictions of several subordinate prediction algorithms, sometimes called “experts.” These simple a...
Yoav Freund, Robert E. Schapire, Yoram Singer, Man...
The study of complex networks led to the belief that the connectivity of network nodes generally follows a Power-law distribution. In this work, we show that modeling large-scale ...
Alessandra Sala, Haitao Zheng, Ben Y. Zhao, Sabrin...