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Alexander Lorbert, Ph.D. - Publications

Affiliations: 
2012 Electrical Engineering Princeton University, Princeton, NJ 
Area:
Biological & Biomedical,Information Sciences & Systems
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8 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2013 Lorbert A, Ramadge PJ. The Pairwise Elastic Net support vector machine for automatic fMRI feature selection Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 1036-1040. DOI: 10.1109/ICASSP.2013.6637807  0.563
2013 Lorbert A, Guntupalli JS, Eis DJ, Haxby JV, Ramadge PJ. Collaborative denoising of multi-subject fMRI data Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 1008-1012. DOI: 10.1109/ICASSP.2013.6637801  0.59
2012 Xu H, Lorbert A, Ramadge PJ, Guntupalli JS, Haxby JV. Regularized hyperalignment of multi-set fMRI data 2012 Ieee Statistical Signal Processing Workshop, Ssp 2012. 229-232. DOI: 10.1109/SSP.2012.6319668  0.595
2012 Lorbert A, Ramadge PJ. Kernel hyperalignment Advances in Neural Information Processing Systems. 3: 1790-1798.  0.628
2011 Lorbert A, Ramadge PJ. The Rotational Lasso Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 3896-3899. DOI: 10.1109/ICASSP.2011.5947203  0.498
2010 Lorbert A, Ramadge PJ. Level set estimation on the sphere Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 2202-2205. DOI: 10.1109/ICASSP.2010.5495725  0.558
2010 Lorbert A, Eis D, Kostina V, Blei DM, Ramadge PJ. Exploiting covariate similarity in sparse regression via the Pairwise Elastic Net Journal of Machine Learning Research. 9: 477-484.  0.57
2010 Lorbert A, Ramadge PJ. Descent methods for tuning parameter refinement Journal of Machine Learning Research. 9: 469-476.  0.458
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