Online learning algorithms have recently risen to prominence due to their strong theoretical guarantees and an increasing number of practical applications for large-scale data ana...
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
A review of research that has been carried out on data mining and visual analysis of movement patterns suggests that there is little agreement on the relevant types of movement pa...
Somayeh Dodge, Robert Weibel, Anna-Katharina Laute...
The method of Moving Least Squares (MLS) is a popular framework for reconstructing continuous functions from scattered data due to its rich mathematical properties and well-underst...
Christian Ledergerber, Gaël Guennebaud, Miriah ...
Clustering ensembles combine different clustering solutions into a single robust and stable one. Most of existing methods become highly time-consuming when the data size turns to ...