Simone Shuheng Zhou

Contact info:

Phone: 734-764-7732
Office: 445B West Hall
Mailing: 439 West Hall
1085 South University Ave.
Ann Arbor, MI 48109

I am an assistant professor of Statistics, and EECS (by courtesy), at the University of Michigan, Ann Arbor.
Most of my recent papers are on arxiv.
Publications by Year/ Publications by Area/ Annotated Bibliography (outdated)/ Google scholar profile

Research Interests

Statistical learning theory and algorithms, convex optimization, decision theory, privacy,
approximation and randomized algorithms, network and combinatorial optimization.

Publications

Gemini: Graph estimation with matrix variate normal instances
Shuheng Zhou. Sept. 23, 2012.
University of Michigan, Department of Statistics, Technical Report 531, 2012.
arxiv 1209.5075
Reconstruction from anisotropic random measurements
Mark Rudelson and Shuheng Zhou.
IEEE Transactions on Information Theory, Volumn 59. No 6, pp 3434--3447.
Extended abstract in COLT 2012, Edinburgh, Scotland.
journal link/ conf version/ arxiv 1106.1151
High-dimensional covariance estimation based on Gaussian graphical models
Shuheng Zhou, Philipp Rutimann, Min Xu, and Peter Buhlmann.
Journal of Machine Learning Research, Volume 12, pp 2975-3026, Oct. 2011.
Journal link/ arxiv 1009.0530
The adaptive and the thresholded Lasso for potentially misspecified models (and a lower bound for the Lasso)
Sara van de Geer, Peter Bühlmann, and Shuheng Zhou.
Electronic Journal of Statistics 2011, Volume 5, pp 688-749.
Journal Link/ arxiv:1001.5176.
Time Varying Undirected Graphs
Shuheng Zhou, John Lafferty and Larry Wasserman.
Machine Learning Journal Vol 80, Numbers 2--3, pp 295--319, Sep. 2010 (invited), special issue for COLT 2008.
Journal link/ conf version/ arxiv:0802.2758
A Statistical Framework for Differential Privacy
Larry Wasserman and Shuheng Zhou.
Journal of the American Statistical Association in Mar 2010, Volume 105, No. 489, pp 375--389.
Journal link (appeared as a featured JASA article) / arxiv:0811.2501
Edge Disjoint Paths in Moderately Connected Graphs
Satish Rao and Shuheng Zhou.
SIAM Journal on Computing, Volume 39, No.5, pp 1856--1887, January, 2010.
Extended abstract in International Colloquium on Automata, Languages and Programming (ICALP 06),
Abstract/ Journal version/ Journal link/ conf version
Thresholded Lasso for high dimensional variable selection and statistical estimation
Shuheng Zhou. February 8, 2010.
University of Michigan, Department of Statistics, Technical Report 511, 2010.
Talk slides, Universite de Paris Est Marne-la-Vallee, May 20, 2010.
arxiv 1002.1583;
Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation
Shuheng Zhou. June 5th, 2009.
Advances in Neural Information Processing Systems 21 (NIPS), pp 2304--2312, December 2009.
PDF/ For full proofs see arxiv 1002.1583.
Compressed and Privacy Sensitive Sparse Regression
Shuheng Zhou, John Lafferty and Larry Wasserman.
IEEE Transactions on Information Theory, Volume 55, No.2, pp 846--866, February 2009.
Extended abstract titled "Compressed Regression" in the 21st Annual Conference on Neural Information Processing Systems.
Journal link/ conf version/ arxiv:0706.0534
Differential Privacy with Compression
Shuheng Zhou, Katrina Ligett and Larry Wasserman.
2009 IEEE International Symposium on Information Theory. Seoul, Korea, June -- July 2009.
arxiv:0901.1365/ conf version
Separating Populations with Wide Data: a Spectral Analysis
with Avrim Blum, Amin Coja-Oghlan, and Alan Frieze.
Electronic Journal of Statistics, Volume 3, pp 76--113, 2009.
Extended abstract in the 18th International Symposium on Algorithms and Computation (ISAAC 2007)
Journal Link/ conf version
A Rigorous Analysis of Population Stratification with Limited Data
with Kamalika Chaudhuri, Eran Halperin, and Satish Rao.
ACM-SIAM Symposium on Discrete Algorithms (SODA) 2007.
PDF
On Hierarchical Routing in Doubling Metrics
with T-H. Hubert Chan, Anupam Gupta and Bruce M. Maggs.
ACM-SIAM Symposium on Discrete Algorithms (SODA) 2005.
Abstract / Postscript [203K] / PDF [199K] (conf version)
Design and Evaluation of an Individually Simulated Mobility Model in Wireless Ad Hoc Networks
Desney S Tan, Shuheng Zhou, Jiann-min Ho, Janek Mehta, Hideaki Tanabe.
Communication Networks and Distributed Systems Modeling and Simulation Conference 2002.
PDF[255K]

Other Manuscripts

Restricted eigenvalue conditions on subgaussian random matrices
Shuheng Zhou. December 20, 2009.
arxiv 0912.4045.
Note: Results are weaker than those in a subsequent paper arxiv 1106.1151
not intended for publication; However, proofs are rather different and quite short.
Adaptive Lasso for high dimensional regression and Gaussian graphical modeling
Shuheng Zhou, Sara van de Geer, and Peter Buhlmann. March 2009.
arxiv:0903.2515.
Note: Part of this paper was superseded by arxiv:1001.5176.
Compressed Lasso is consistent
Shuheng Zhou. Manuscript, 2009. (In permanent preparation)
Differential privacy for continuous data
with Larry Wasserman. July 2008.
Quantization and the privacy-accuracy tradeoff
with Stephen Fienberg, Yuval Nardi, Alessandro Rinaldo, Larry Wasserman. June 2008.
Learning balanced mixtures of discrete distributions with small sample
Shuheng Zhou. Feburary 2008. (Results included in my thesis, written here for reference).
arxiv:0802.1244.

Thesis and Technical Reports

Routing, Disjoint Paths, and Classification
Carnegie Mellon University Ph.D. Dissertation CMU-PDL-06-109, August 2006.
(This contains results in my SODA05, ICALP06, SODA07 papers and arxiv:0802.1244 preprint.)
Abstract/ Postscript [1.1M]/ PDF [971K]
Balancing Locality and Randomness in DHTs
Shuheng Zhou, Gregory R. Ganger, Peter Steenkiste.
Carnegie Mellon University Technical Report CMU-CS-03-203, November 2003.
Abstract / Postscript [489K] / PDF [511K]
Location-based Node IDs: Enabling Explicit Locality in DHTs
Shuheng Zhou, Gregory R. Ganger, Peter Steenkiste.
Carnegie Mellon University Technical Report CMU-CS-03-171, September 2003.
Abstract / Postscript [282K] / PDF [160K]

Teaching

Statistics 605: Advanced Topics in Modeling and Data Analysis (Winter 2012)
Lectures: M W 11:30 am - 1:00pm in Dennison 110.

Statistics 711, Special Topics in Theoretical Statistics II:
High dimensional statistical inference (Winter 2011).

Statistics 426: Introduction to Theoretical Statistics (Fall 2011,10)
Lectures: T Th 2:30pm -4:00pm in Dennison 245.

Bio

In Spring 2010, I was a visiting scholar with Department of Statistics, UC. Berkeley, hosted by Professor Bin Yu. I was a postdoc fellow with the Seminar for Statistics in Department of Mathematics at ETH Zurich between August 2008 and June 2010, and in the Computer Science Department at CMU from Sep. 2006 to July 2008. I worked closely with Professors John Lafferty and Larry Wasserman on Statistical and Machine Learning theory and algorithms, and Privacy. In a previous life, I was a graduate student at CMU, advised by Professors Greg Ganger and Bruce Maggs on theoretical computer science. I was affiliated with the Parallel Data Lab.

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