-- Combination of multiple clusterings is an important task in the area of unsupervised learning. Inspired by the success of supervised bagging algorithms, we propose a resampling ...
Behrouz Minaei-Bidgoli, Alexander P. Topchy, Willi...
Efficient task scheduling is essential for obtaining high performance in heterogeneous distributed computing systems (or HeDCSs). Because of its key importance, several scheduling...
Commodity symmetric multiprocessors (SMPs), though originally intended for transaction processing, because of their availability, are now used for numerical analysis applications ...
We consider the problem of quantizing data generated from disparate sources, e.g. subjects performing actions with different styles, movies with particular genre bias, various con...
Ekaterina Taralova, Fernando DelaTorre, Martial He...
Slice sampling provides an easily implemented method for constructing a Markov chain Monte Carlo (MCMC) algorithm. However, slice sampling has two major drawbacks: (i) it requires...