We present a multi-label multiple kernel learning (MKL) formulation in which the data are embedded into a low-dimensional space directed by the instancelabel correlations encoded ...
We consider the problem of multiple kernel learning (MKL), which can be formulated as a convex-concave problem. In the past, two efficient methods, i.e., Semi-Infinite Linear Prog...
In this paper we describe the problem of Optimal Competitive Scheduling, which consists of activities that compete for a shared resource. The objective is to choose a subset of ac...
Jeremy Frank, James Crawford, Lina Khatib, Ronen I...
Information visualisation exploits the natural perceptual capabilities of the decisionfacilitate the rapid assimilation and analysis of abstract, complex and often voluminous info...
Tim Pattison, Rudi Vernik, Daniel Goodburn, Matthe...
AdaBoost rarely suffers from overfitting problems in low noise data cases. However, recent studies with highly noisy patterns clearly showed that overfitting can occur. A natural s...