Vincent Q. Vu

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Jing LeiCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Bin YUProfessor of Statistics and EECS, UC BerkeleyVerified email at stat.berkeley.edu
Robert E. KassMaurice Falk Professor of Statistics and Computational Neuroscience, Carnegie Mellon UniversityVerified email at stat.cmu.edu
Karl RoheProfessor of Statistics, UW MadisonVerified email at stat.wisc.edu
Pradeep RavikumarProfessor, School of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Thomas NaselarisAssociate Professor, Department of Neuroscience, University of MinnesotaVerified email at umn.edu
Kendrick KayAssociate Professor, University of MinnesotaVerified email at umn.edu
Jack L. GALLANTUniversity of California at BerkeleyVerified email at berkeley.edu
Guanhua YanDepartment of Computer Science, Binghamton University, State University of New YorkVerified email at binghamton.edu
Stephan EidenbenzComputer Science, Los Alamos National LaboratoryVerified email at lanl.gov
Nicolas W HengartnerLos Alamos National LaboratoryVerified email at lanl.gov
Sagi PerelResearch Engineer, Google DeepmindVerified email at google.com
Andrew B. SchwartzProfessor of Neurobiology, University of PittsburghVerified email at pitt.edu

Vincent Q. Vu

Associate Professor of Statistics, The Ohio State University

Verified email at stat.osu.edu - Homepage

statistics machine learning computation


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Minimax sparse principal subspace estimation in high dimensions VQ Vu, J Lei Annals of Statistics 41 (6), 2905-2947, 2013	238	2013
Fantope Projection and Selection: A near-optimal convex relaxation of sparse PCA VQ Vu, J Cho, J Lei, K Rohe Advances in Neural Information Processing Systems (NIPS) 26, 2670-2678, 2013	213	2013
Minimax rates of estimation for sparse pca in high dimensions VQ Vu, J Lei Artificial Intelligence and Statistics (AISTATS) 15, 2012	154	2012
Bluetooth worm propagation: mobility pattern matters! G Yan, HD Flores, L Cuellar, N Hengartner, S Eidenbenz, V Vu Proceedings of the 2nd ACM symposium on Information, computer and …, 2007	90	2007
Coverage‐adjusted entropy estimation VQ Vu, B Yu, RE Kass Statistics in medicine 26 (21), 4039-4060, 2007	69	2007
Sparsistency and agnostic inference in sparse PCA J Lei, VQ Vu Annals of Statistics, 2015	68	2015
Encoding and decoding V1 fMRI responses to natural images with sparse nonparametric models VQ Vu, P Ravikumar, T Naselaris, KN Kay, JL Gallant, B Yu The Annals of Applied Statistics 5 (2B), 1159-1182, 2011	47	2011
Information in the nonstationary case VQ Vu, B Yu, RE Kass Neural computation 21 (3), 688-703, 2009	28	2009
A multivariate Gaussian process factor model for hand shape during reach-to-grasp movements L Castellanos, VQ Vu, S Perel, AB Schwartz, RE Kass Statistica Sinica, 2015	14	2015
Squared-norm empirical processes VQ Vu, J Lei Statistics & Probability Letters 150, 108-113, 2019	6*	2019
Nonparametric sparse hierarchical models describe v1 fmri responses to natural images P Ravikumar, V Vu, B Yu, T Naselaris, K Kay, J Gallant, C Berkeley Advances in Neural Information Processing Systems (NIPS) 21, 2008	5*	2008
Computational Sufficiency, Reflection Groups, and Generalized Lasso Penalties VQ Vu arXiv preprint arXiv:1809.02857, 2018	2	2018
Group Invariance and Computational Sufficiency VQ Vu arXiv preprint arXiv:1807.05985, 2018	2	2018
Some statistical issues in estimating information in neural spike trains VQ Vu, B Yu, RE Kass 2009 IEEE International Conference on Acoustics, Speech and Signal …, 2009	1	2009
High dimensional estimation and data analysis: Entropy and regularized regression VQ Vu University of California, Berkeley, 2009		2009

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