Efficient Inference in Matrix-Variate Gaussian Models with i.i.d. Observation Noise

[edit]

Oliver Stegle, European Bioinformatics Institute
Christoph Lippert, Human Longevity, Inc
Joris Mooij
Neil D. Lawrence, University of Sheffield
Karsten Borgwardt, ETH Zurich

in Neural Information Processing Systems

Abstract


@InProceedings{stegle-sparse11,
  title = 	 {Efficient Inference in Matrix-Variate Gaussian Models with i.i.d. Observation Noise},
  author = 	 {Oliver Stegle and Christoph Lippert and Joris Mooij and Neil D. Lawrence and Karsten Borgwardt},
  booktitle = 	 {Neural Information Processing Systems},
  year = 	 {2011},
  month = 	 {00},
  edit = 	 {https://github.com/lawrennd//publications/edit/gh-pages/_posts/2011-01-01-stegle-sparse11.md},
  url =  	 {http://inverseprobability.com/publications/stegle-sparse11.html},
  abstract = 	 {},
  key = 	 {Stegle:sparse11},
  OPTgroup = 	 {}
 

}
%T Efficient Inference in Matrix-Variate Gaussian Models with i.i.d. Observation Noise
%A Oliver Stegle and Christoph Lippert and Joris Mooij and Neil D. Lawrence and Karsten Borgwardt
%B 
%C Neural Information Processing Systems
%D 
%F stegle-sparse11	
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TY  - CPAPER
TI  - Efficient Inference in Matrix-Variate Gaussian Models with i.i.d. Observation Noise
AU  - Oliver Stegle
AU  - Christoph Lippert
AU  - Joris Mooij
AU  - Neil D. Lawrence
AU  - Karsten Borgwardt
BT  - Neural Information Processing Systems
PY  - 2011/01/01
DA  - 2011/01/01	
ID  - stegle-sparse11	
SP  - 
EP  - 
UR  - http://inverseprobability.com/publications/stegle-sparse11.html
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Stegle, O., Lippert, C., Mooij, J., Lawrence, N.D. & Borgwardt, K.. (2011). Efficient Inference in Matrix-Variate Gaussian Models with i.i.d. Observation Noise. Neural Information Processing Systems :-