Shuheng Zhou I am with the Seminar for Statistics in Department of Mathematics as a postdoc at ETH Zurich since August 2008. I was a postdoc fellow 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. Email: my-login-id@cs.cmu.edu Current contact info

Preprints

• Adaptive Lasso for High Dimensional Regression and Gaussian Graphical Modeling
  Shuheng Zhou, Sara van de Geer and Peter Buhlmann. March 2009.
  arxiv:0903.2515.

Publications

• Thresholding Procedures for High Dimensional Variable Selection and Statistical Estimation
  Shuheng Zhou. June 5th, 2009.
  To appear in the 23rd Annual Conference on Neural Information Processing Systems.
  Vancouver, BC, Canada. December 2009.
  (Paper is in preparation, links coming soon.)

• A Statistical Framework for Differential Privacy
  Larry Wasserman and Shuheng Zhou. November 2008; Revised October, 2009.
  To appear, Journal of the American Statistical Association, in the Theory and Methods section.
  arxiv:0811.2501.

• Differential Privacy with Compression
  Shuheng Zhou, Katrina Ligett and Larry Wasserman.
  In 2009 IEEE International Symposium on Information Theory.
  Seoul, Korea, June -- July 2009.
  arxiv:0901.1365/ conf version

• Time Varying Undirected Graphs
  Shuheng Zhou, John Lafferty and Larry Wasserman.
  To appear in Machine Learning Journal (invited), special issue for the 21st Annual Conference on Learning Theory (COLT 2008).
  Helsinki, Finland, July 2008.
  arXiv:0802.2758/ conf version

• Compressed and Privacy Sensitive Sparse Regression
  Shuheng Zhou, John Lafferty and Larry Wasserman.
  IEEE Transactions on Information Theory, Vol.55, No.2, Pages: 846 -866, February 2009.
  Extended abstract titled "Compressed Regression" in the 21st Annual Conference on Neural Information Processing Systems.
  Vancouver, BC, Canada. December 2007.
  arXiv:0706.0534/ conf version
  

• Edge Disjoint Paths in Moderately Connected Graphs
  with Satish Rao.
  To appear, SIAM Journal on Computing. Revised version May 14th, 2009.
  Extended abstract in International Colloquium on Automata, Languages and Programming (ICALP 06),
  Venice, Italy. July 2006.
  Abstract/ Postscript/ PDF (conf)

• Separating Populations with Wide Data: a Spectral Analysis
  with Avrim Blum, Amin Coja-Oghlan, and Alan Frieze.
  Electronic Journal of Statistics, Volume 3, Pages: 76-113, 2009.
  Extended abstract in the 18th International Symposium on Algorithms and Computation (ISAAC 2007).
  Sendai, Japan, December 2007.
  journal/ conf version

• A Rigorous Analysis of Population Stratification with Limited Data
  with Kamalika Chaudhuri, Eran Halperin, and Satish Rao.
  In ACM-SIAM Symposium on Discrete Algorithms (SODA) 2007.
  New Orleans, Louisiana. January 2007.
  conf version

• On Hierarchical Routing in Doubling Metrics
  with T-H. Hubert Chan, Anupam Gupta and Bruce M. Maggs.
  In submission to SIAM Journal on Computing, 2009. (Link coming soon.)
  In ACM-SIAM Symposium on Discrete Algorithms (SODA) 2005,
  Vancouver, BC, Canada. January 2005.
  Abstract / Postscript [203K] / PDF [199K]
  TR CMU-PDL-04-106 contains an updated version on routing, December 2004

• 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]

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]

• Learning Balanced Mixtures of Discrete Distributions with Small Sample
  Shuheng Zhou. arXiv:0802.1244.
  (Results included in my thesis, written here for reference).

• 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]

Other Manuscripts

• 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.
  

The wise find pleasure in water; the virtuous find pleasure in hills.
The wise are active; the virtuous are tranquil.
The wise are joyful; the virtuous are long-lived.
				-- The Analects, Confucius (551--479 BCE)

Astronomy picture of the day

Last updated: 09/09/09 @Copyright by Shuheng Zhou, 2000 - 2009, all rights reserved