Vincent Q. Vu 个人学术档案

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Jing LeiCarnegie Mellon University在 andrew.cmu.edu 的电子邮件经过验证
Bin YUProfessor of Statistics and EECS, UC Berkeley在 stat.berkeley.edu 的电子邮件经过验证
Robert E. KassMaurice Falk Professor of Statistics and Computational Neuroscience, Carnegie Mellon University在 stat.cmu.edu 的电子邮件经过验证
Karl RoheProfessor of Statistics, UW Madison在 stat.wisc.edu 的电子邮件经过验证
Pradeep RavikumarProfessor, School of Computer Science, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Thomas NaselarisAssociate Professor, Department of Neuroscience, University of Minnesota在 umn.edu 的电子邮件经过验证
Kendrick KayAssociate Professor, University of Minnesota在 umn.edu 的电子邮件经过验证
Jack L. GALLANTUniversity of California at Berkeley在 berkeley.edu 的电子邮件经过验证
Guanhua YanDepartment of Computer Science, Binghamton University, State University of New York在 binghamton.edu 的电子邮件经过验证
Stephan EidenbenzComputer Science, Los Alamos National Laboratory在 lanl.gov 的电子邮件经过验证
Nicolas W HengartnerLos Alamos National Laboratory在 lanl.gov 的电子邮件经过验证
Sagi PerelResearch Engineer, Google Deepmind在 google.com 的电子邮件经过验证
Andrew B. SchwartzProfessor of Neurobiology, University of Pittsburgh在 pitt.edu 的电子邮件经过验证

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Vincent Q. Vu

Associate Professor of Statistics, The Ohio State University

在 stat.osu.edu 的电子邮件经过验证 - 首页

statistics machine learning computation


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Minimax sparse principal subspace estimation in high dimensions VQ Vu, J Lei Annals of Statistics 41 (6), 2905-2947, 2013	231	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	207	2013
Minimax rates of estimation for sparse pca in high dimensions VQ Vu, J Lei Artificial Intelligence and Statistics (AISTATS) 15, 2012	149	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
Sparsistency and agnostic inference in sparse PCA J Lei, VQ Vu Annals of Statistics, 2015	67	2015
Coverage‐adjusted entropy estimation VQ Vu, B Yu, RE Kass Statistics in medicine 26 (21), 4039-4060, 2007	67	2007
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	46	2011
Information in the nonstationary case VQ Vu, B Yu, RE Kass Neural computation 21 (3), 688-703, 2009	26	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		2009
High dimensional estimation and data analysis: Entropy and regularized regression VQ Vu University of California, Berkeley, 2009		2009

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