Abstract. This paper studies a risk minimization approach to estimate a transformation model from noisy observations. It is argued that transformation models are a natural candidat...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
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 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. ...
While the web provides information and services that enrich our lives in many ways, it has also become the primary vehicle for delivering malware. Once infected with web-based mal...