Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
This work introduces distance-based criteria for segmentation of object trajectories. Segmentation leads to simplification of the original objects into smaller, less complex primi...
The problem of assessing the significance of data mining results on high-dimensional 0?1 data sets has been studied extensively in the literature. For problems such as mining freq...
Aristides Gionis, Heikki Mannila, Panayiotis Tsapa...
Learning ranking (or preference) functions has been a major issue in the machine learning community and has produced many applications in information retrieval. SVMs (Support Vect...