We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...
When computer intrusions occur, one of the most costly, time-consuming, and human-intensive tasks is the analysis and recovery of the compromised system. At a time when the cost o...
Ashvin Goel, Wu-chang Feng, David Maier, Wu-chi Fe...
Background modeling is an important component of many vision systems. Existing work in the area has mostly addressed scenes that consist of static or quasi-static structures. When...
We propose a novel privacy-preserving nonlinear support vector machine (SVM) classifier for a data matrix A whose columns represent input space features and whose individual rows ...
In this paper, we introduce two new formulations for multi-class multi-kernel relevance vector machines (mRVMs) that explicitly lead to sparse solutions, both in samples and in nu...
Theodoros Damoulas, Yiming Ying, Mark A. Girolami,...