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This thesis is devoted to information-theoretic aspects of community detection. The importance of community detection is due to the massive amount of scientific data today that describes relationships between items from a network, e.g., a social network. I ...
Angiogenesis inhibitory drug combination obtained according to a specific algorithm, preferably a FSC, in which an initial combination of drugs is iteratively adjusted. The drug combination according to the invention may advantageously comprise a RAPTA-C c ...
A CUR approximation of a matrix A is a particular type of low-rank approximation where C and R consist of columns and rows of A, respectively. One way to obtain such an approximation is to apply column subset selection to A and its transpose. In this work, ...
Knapsack and Subset Sum are fundamental NP-hard problems in combinatorial optimization. Recently there has been a growing interest in understanding the best possible pseudopolynomial running times for these problems with respect to various parameters. In t ...
Schloss Dagstuhl -- Leibniz-Zentrum für Informatik2021
(1) Understanding tree seedling responses to water, nutrient, and light availability is crucial to precisely predict potential shifts in composition and structure of forest communities under future climatic conditions. (2) We exposed seedlings of widesprea ...
We propose a non-intrusive reduced basis (RB) method for parametrized nonlinear partial differential equations (PDEs) that leverages models of different accuracy. The method extracts parameter locations from a collection of low-fidelity (LF) snapshots for ...
A sample of contracts of apprenticeship from three periods in the history of early modern Venice is analysed, as recorded in the archive of the Giustizia Vecchia, a venetian magistracy. The periods are the end of the 16th century, the 1620s and the 1650s. ...
We use a combination of extreme value statistics, survival analysis and computer-intensive methods to analyse the mortality of Italian and French semi-supercentenarians. After accounting for the effects of the sampling frame, extreme-value modelling leads ...
Diffusion adaptation is a powerful strategy for distributed estimation and learning over networks. Motivated by the concept of combining adaptive filters, this work proposes a combination framework that aggregates the operation of multiple diffusion strate ...