In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
We consider the following fundamental scheduling problem. The input consists of n jobs to be scheduled on a set of machines of bounded capacities. Each job is associated with a re...
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
The Minimax Probability Machine (MPM) constructs a classifier, which provides a worst-case bound on the probability of misclassification of future data points based on reliable ...
Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. ...
Sharing selected data structures among virtual machines of a safe language can improve resource utilization of each participating run-time system. The challenge is to determine wh...
Bernard Wong, Grzegorz Czajkowski, Laurent Dayn&eg...