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ICML
2005
IEEE
15 years 10 months ago
Healing the relevance vector machine through augmentation
The Relevance Vector Machine (RVM) is a sparse approximate Bayesian kernel method. It provides full predictive distributions for test cases. However, the predictive uncertainties ...
Carl Edward Rasmussen, Joaquin Quiñonero Ca...
KDD
2005
ACM
193views Data Mining» more  KDD 2005»
15 years 10 months ago
An approach to spacecraft anomaly detection problem using kernel feature space
Development of advanced anomaly detection and failure diagnosis technologies for spacecraft is a quite significant issue in the space industry, because the space environment is ha...
Ryohei Fujimaki, Takehisa Yairi, Kazuo Machida
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
15 years 10 months ago
Transforming data to satisfy privacy constraints
Data on individuals and entities are being collected widely. These data can contain information that explicitly identifies the individual (e.g., social security number). Data can ...
Vijay S. Iyengar
SDM
2009
SIAM
180views Data Mining» more  SDM 2009»
15 years 7 months ago
Hierarchical Linear Discriminant Analysis for Beamforming.
This paper demonstrates the applicability of the recently proposed supervised dimension reduction, hierarchical linear discriminant analysis (h-LDA) to a well-known spatial locali...
Barry L. Drake, Haesun Park, Jaegul Choo
SENSYS
2009
ACM
15 years 4 months ago
Darjeeling, a feature-rich VM for the resource poor
The programming and retasking of sensor nodes could benefit greatly from the use of a virtual machine (VM) since byte code is compact, can be loaded on demand, and interpreted on...
Niels Brouwers, Koen Langendoen, Peter Corke