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JMLR
2010
152views more  JMLR 2010»
15 years 12 days ago
Bayesian Generalized Kernel Models
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. ...
ICDCSW
2005
IEEE
15 years 11 months ago
Forensix: A Robust, High-Performance Reconstruction System
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...
CVPR
2004
IEEE
16 years 7 months ago
Motion-Based Background Subtraction Using Adaptive Kernel Density Estimation
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...
Anurag Mittal, Nikos Paragios
DMIN
2008
145views Data Mining» more  DMIN 2008»
15 years 7 months ago
Privacy-Preserving Classification of Horizontally Partitioned Data via Random Kernels
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 ...
Olvi L. Mangasarian, Edward W. Wild
ICMLA
2008
15 years 7 months ago
Inferring Sparse Kernel Combinations and Relevance Vectors: An Application to Subcellular Localization of Proteins
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,...