A hyper-heuristic performs search over a set of other search mechanisms. During the search, it does not require any problem-dependent data. This structure makes hyperheuristics pro...
Mustafa Misir, Katja Verbeeck, Patrick De Causmaec...
We present a probabilistic model for clustering of objects represented via pairwise dissimilarities. We propose that even if an underlying vectorial representation exists, it is b...
Julia E. Vogt, Sandhya Prabhakaran, Thomas J. Fuch...
Identifying the most influential documents in a corpus is an important problem in many fields, from information science and historiography to text summarization and news aggregati...
Gaussian mixture models (GMMs) are a convenient and essential tool for the estimation of probability density functions. Although GMMs are used in many research domains from image ...
In this paper, we are interested in the analysis of regularized online algorithms associated with reproducing kernel Hilbert spaces. General conditions on the loss function and st...