P. Ravikumar, M. J. Wainwright, G. Raskutti and B. Yu.
High-dimensional covariance estimation by minimizing $\ell_1$-penalized log-determinant divergence. Arxiv Paper. Presented in
part the NIPS Conference. December, 2008, Vancouver, Canada.
M. J. Wainwright and M. I. Jordan
Graphical models, exponential families, and variational inference.
Foundations and Trends in Machine Learning, Vol. 1, Numbers 1--2, pp. 1--305,
December 2008.
Full Text (2M pdf)
Preliminary versions:
M. J. Wainwright, and M. I. Jordan.
Variational inference in graphical models: The view from the marginal
polytope. Invited paper; Allerton Conference on
Communication, Control, and Computing; October 1--3, 2003;
Urbana-Champaign, IL
M. J. Wainwright, and M. I. Jordan. Graphical
models, exponential families, and variational inference. UC
Berkeley, Dept. of Statistics, Technical Report 649. September, 2003.
N. Santhanam and M. J. Wainwright.
Information-theoretic limits of selecting binary graphical models
in high dimensions Technical report:
Arxiv preprint (PDF)
Preliminary version presented at International Symposium on Information Theory (ISIT), Toronto, Canada. July, 2008.
P. Ravikumar, A. Agarwal and M. J. Wainwright.
Message-passing for graph-structured linear programs: Proximal projections,
convergence, and rounding schemes. To appear in International
Conference on Machine Learning (ICML), Helsinki, Finland. July, 2008.
T. G. Roosta, M. J. Wainwright and S. S. Sastry. Convergence analysis of reweighted sum-product algorithms.
IEEE Trans. Signal Processing 56(9): 4293--4305, September 2008.
Full Text (1.2M pdf)
P. Ravikumar, M. J. Wainwright and J. Lafferty. High-dimensional Ising model
selection using $\ell_1$-regularized logistic regression. To appear
in the Annals of Statistics.
Full Text (PDF).
Preliminary versions:
Department of Statistics, Technical Report 750, April 2008.
M. J. Wainwright, P. Ravikumar and J. Lafferty.
Advances in Neural Information Processing Systems, December
2006. Vancouver. Canada.
E. B. Sudderth, M. J. Wainwright, and A. S. Willsky
Loop series and Bethe variational bounds in attractive graphical
models. Proceedings of the NIPS conference, Vancouver,
Canada. December 2007.
Full Text (152K pdf) .
M. J. Wainwright. Estimating the ``wrong'' graphical model:
Benefits in the computation-limited setting. Journal of Machine
Learning Research, 7:1829--1859. September 2006.
Full Text (343K pdf) .
Preliminary versions:
M. J. Wainwright.
NIPS Conference, December 2005, Vancouver, Canada.
M. J. Wainwright and M. I. Jordan, Log-determinant relaxation for approximate inference in discrete Markov random fields.
IEEE Transactions on
Signal Processing, Vol. 54(6), pages 2099--2109. June 2006.
Full Text (869K ps) / Full Text (301K pdf)
Preliminary versions:
Appeared previously as UC Berkeley, Department of EECS, Technical Report UCB/CSD-3-1226, January 2003 (outdated).
M. J. Wainwright and M. I. Jordan. NIPS Conference, December 2003, Vancouver, Canada.
E. Maneva, E. Mossel and M. J. Wainwright.
A New Look at Survey Propagation and its Generalizations.
Journal of the ACM, Volume 54(4), July 2007. pp. 2--41.
Full Text (PDF)
Preliminary version:
Extended abstract at Symposium on Discrete
Algorithms (SODA), January 2005, Vancouver, Canada.
V. N. Kolmogorov and M. J. Wainwright. On optimality of
tree-reweighted max-product message-passing. Appeared in
Uncertainty in Artificial Intelligence, July 2005, Edinburgh, Scotland.
M. J. Wainwright, T. S. Jaakkola and A. S. Willsky, MAP
estimation via agreement on (hyper)trees: Message-passing and
linear-programming approaches. IEEE Transactions on
Information Theory, Vol. 51(11), pages 3697--3717. November 2005.
Full Text (719K pdf)
Preliminary versions:
M. J. Wainwright, T. Jaakkola and A. S. Willsky.
Exact MAP estimates by (hyper)tree agreement. NIPS conference; December, 2002; Vancouver, BC, Canada.
M. J. Wainwright, T. Jaakkola and A. S. Willsky.
MAP estimation via agreement on (hyper)trees: Message-passing
and linear programming approaches.
Allerton Conference on Communication, Control,
and Computing; October 2--4, 2002; Urbana-Champaign, IL
M. J. Wainwright and M. I. Jordan.
Treewidth-based conditions for exactness of the Sherali-Adams and
Lasserre relaxations. UC Berkeley,
Dept. of Statistics, Technical Report 671. September, 2004.
M. J. Wainwright, T. Jaakkola and A. S. Willsky.
A new class of upper bounds on the log partition function.
IEEE Trans. on Information Theory, vol. 51, page 2313--2335, July 2005.
Full Text (378K pdf)
Preliminary versions:
M. J. Wainwright, T. Jaakkola and A. S. Willsky.
Uncertainty in Artificial Intelligence; August 1--4, 2002;
Edmonton, CA. Best Paper Award Full Text (296K pdf)
M. J. Wainwright, T. Jaakkola and A. S. Willsky.
Tree-reweighted belief propagation and approximate ML estimation by
pseudo-moment matching. Presented at the 9th Workshop on
Artificial Intelligence and Statistics, Key West, Florida; January,
2003 Abstract
/ Full Text (352K ps) /
Full Text (352K pdf)
M. J. Wainwright, T. Jaakkola and A. S. Willsky.
Tree consistency and bounds on the performance of the
max-product algorithm and its generalizations. Statistics and
Computing, April 2004, Vol. 14, 143--166.
Journal version: Full Text (446K pdf)
M. J. Wainwright, T. Jaakkola and A. S. Willsky.
Tree-based reparameterization framework for analysis of sum-product and related algorithms. IEEE Transactions on Information Theory, 45(9): pages 1120--1146.
Originally appeared as LIDS Technical Report P-2510; Laboratory for
Information and Decision Systems, MIT, May 2001.
Local PDF file
/
Link to paper on IEEE Xplore
Preliminary version:
M. J. Wainwright, T. Jaakkola
and A. S. Willsky. Tree-based reparameterization for
approximate estimation on graphs with cycles. Presented at
the Conference on Neural Information Processing Systems (NIPS).
Vancouver, Canada. Dec 3--8, 2001. Published in Advances in Neural
Information Processing Systems 14; MIT Press, Cambridge MA, May 2002.
Runner-up Best Student Paper Award
E. Sudderth, M. J. Wainwright and A. S. Willsky.
Embedded trees: Estimation of Gaussian processes on graphs with
cycles. IEEE Transactions on Signal Processing, November
2004, Vol. 52, pp. 3136 --3150.
Journal version: Full Text (770K pdf)
Preliminary version:
M. J. Wainwright,
E. Sudderth and A. S. Willsky. Tree-based modeling and
estimation of Gaussian processes on graphs with cycles.
Presented at the Conference on Neural Information Processing Systems
(NIPS). Denver, CO. Nov. 28--30, 2000.
G. Raskutti, M. J. Wainwright and B. Yu.
Minimax rates of estimation for high-dimensional linear regression over $\ell_q$-balls.
Arxiv paper.
Presented in part at the Allerton Conference on Control, Communication and
Computing, September 2009, Monticello, IL.
S. Negahban and M. J. Wainwright,
Simultaneous support recovery in high dimensions: Benefits and perils of block $\ell_1/\ell_\infty$-regularization
UC Berkeley Technical Report 774, May 2009.
Full Text (181K pdf).
Preliminary versions:
Joint support recovery under
high-dimensional scaling: Benefits and perils of
$\ell_{1,\infty}$-regularization. Advances in Neural Information
Processing Systems, December 2008. Vancouver. Canada
M. J. Wainwright, Sharp thresholds for noisy
and high-dimensional recovery of sparsity using $\ell_1$-constrained
quadratic programming )Lasso) , IEEE Transactions on
Information Theory, 55:2183--2202, May 2009.
Full Text (PDF)
Preliminary versions:
Technical report 709,
Department of Statistics, UC Berkeley. May 2006.
Short version presented at
Allerton Conference on Communication, Control and Computing, September 2006.
Arash A. Amini and M. J. Wainwright,
High-dimensional analysis of semidefinite programming relaxations for
sparse principal component analysis. 37(5B): 2877-2921, 2009.
Full Text (PDF)
Preliminary versions:
Technical report 747,
Department of Statistics, UC Berkeley. March 2008.
Short version presented at International Symposium on Information Theory (ISIT), Toronto, Canada. July, 2008
P. Ravikumar, M. J. Wainwright, G. Raskutti and
B. Yu. High-dimensional covariance estimation by minimizing
$\ell_1$-penalized log-determinant
divergence. Arxiv
Paper.
Preliminary version:
Presented in part the NIPS Conference. December, 2008, Vancouver,
Canada.
P. Ravikumar, M. J. Wainwright and J. Lafferty. High-dimensional Ising model
selection using $\ell_1$-regularized logistic regression. To appear
in the Annals of Statistics.
Full Text (PDF).
Preliminary versions:
Department of Statistics, Technical Report 750, April 2008.
M. J. Wainwright, P. Ravikumar and J. Lafferty.
Advances in Neural Information Processing Systems, December
2006. Vancouver. Canada.
G. Obozinski and M. J. Wainwright, and M. I. Jordan
Union support recovery in high-dimensional multivariate regression.
UC Berkeley Technical Report 761, August 2008.
Full Text (181K pdf).
W. Wang, M. J. Wainwright and K. Ramchandran.
Information-theoretic limits on sparse signal recovery: Dense versus sparse
measurement matrices.
UC Berkeley Technical Report 754, May 2008.
Full Text (181K pdf).
Short version presented at International Symposium on Information Theory (ISIT), Toronto, Canada. July, 2008
D. Omidiran and M. J. Wainwright.
High-dimensional subset recovery in noise: Sparsified measurements without loss of
statistical efficiency.
UC Berkeley Technical Report 753, May 2008.
Full Text (181K pdf).
Short version presented at International Symposium on Information Theory (ISIT), Toronto, Canada. July, 2008
N. Santhanam and M. J. Wainwright.
Information-theoretic limits of selecting binary graphical models
in high dimensions Technical report:
Arxiv preprint (PDF)
Preliminary version presented at International Symposium on Information Theory (ISIT), Toronto, Canada. July, 2008.
M. J. Wainwright, Information-theoretic
limits on sparsity recovery in the high-dimensional
and noisy setting. Technical report 725,
Department of Statistics, UC Berkeley. January 2007.
Full Text (181K pdf) Presented in part at International Symposium on
Information Theory (ISIT), Nice, France, July 2007.
X. Nguyen, M. J. Wainwright and M. I. Jordan.
On divergences, surrogate loss functions, and f-divergences.
Annals
of Statistics, 37(2): 876--904 (2009).
Full Text (348K pdf)
Preliminary version:
UC Berkeley Department of Statistics, Technical Report 695, October 2005.
X. Nguyen, M. J. Wainwright and M. I. Jordan.
43rd Annual Allerton Conference on Communication, Control and Computing, IL, September 2005.
X. Nguyen, M. J. Wainwright and M. I. Jordan,
On optimal quantization rules for some problems in sequential
decentralized detection. IEEE Transactions on Information Theory,
Vol. 54(7), pp. 3285--3295. July 2008.
Full Text (PDF)
Preliminary versions:
Presented in part at
International Symposium on Information Theory, Seattle, WA. July 2006.
Longer version appeared originally as
Technical Report 708, Department of Statistics, UC Berkeley. August 2006.
R. Rajagopal and M. J. Wainwright.
Network-based consensus averaging with general noisy channels.
Department of Statistics, Technical Report 751, May 2008. Presented in part at
Allerton Conference on Control, Communication, and Computing (Sep. 2007).
Full Text (1.6M pdf)
A. G. Dimakis, A. Sarwate and M. J. Wainwright.
Geographic Gossip: Efficient Averaging for Sensor Networks.
IEEE Transactions on Signal Processing, 53: 1205--1216. March 2008.
Full Text (1.2M pdf)
Conference version:
Fifth International Conference on Information Processing in Sensor
Networks (IPSN), Nashville, TN. April 2006.
M. Cetin, L. Chen, J. Fisher, A. Ihler, R. Moses,
M. J. Wainwright and A. S. Willsky. Distributed fusion in sensor networks. IEEE Signal Processing Magazine, July 2006.
Full Text (1M pdf)
R. Rajagopal, M. J. Wainwright and P. Varaiya,
Universal Quantile Estimation with Feedback in the Communication-Constrained Setting,
International Symposium on Information Theory, Seattle, WA. July 2006.
Full Text (148K pdf)
X. Nguyen, M. J. Wainwright and M. I Jordan.
Nonparametric decentralized detection using kernel methods.
IEEE Transactions on Signal Processing, Vol. 53(11),
pages 4053--4066. November 2005.
IEEE Signal Processing Outstanding Young Author Award (XuanLong Nguyen)
Full Text (754K pdf)
Preliminary versions:
X. Nguyen, M. J. Wainwright and M. I Jordan.
Decentralized detection and classification using kernel methods.
Proceedings of the International Conference on Machine Learning,
July
2004. Outstanding Student Paper Award (XuanLong Nguyen)
Full Text (204K pdf)
Technical report, UC Berkeley,
Dept. of Statistics, Technical Report 658. April, 2004.
L. Chen, M. Wainwright, M. Cetin and A. Willsky,
Multitarget-multisensor data association using the tree-reweighted max-product algorithm.
Presented at the SPIE Aerosense conference, Orlando, FL,
March
2003. Full Text (204K pdf) \
Full Text (204K pdf)
A. G.. Dimakis, A. A. Gohari and M. J. Wainwright,
Guessing Facets: Polytope Structure and Improved LP Decoding.
IEEE Transactions on Information Theory. 55(8):3479--3478, August 2009.
Full Text (pdf)
Preliminary version:
International Symposium on Information Theory, Seattle, WA. July
2006.
L. Dolecek, P. Lee, Z. Zhang, V. Anatharam, B. Nikolic
and M. J. Wainwright. Predicting error floors of structured
LDPC codes: Deterministic bounds and estimates.
IEEE Journal on Selected Areas in Communications, 27(6):908--917,
August 2009.
Full text (PDF)
Preliminary version:
P. Lee, L. Dolecek, Z. Zhang, V. Anantharam, B. Nikolic and M. J .
Wainwright, Error Floors in LDPC Codes: Fast Simulation, Bounds and Hardware Emulation . IEEE International Symposium on Information Theory (ISIT 2008), Toronto, Canada, July 2008.
Full Text (PDF)
M. J. Wainwright and E. Martinian, Low-density
graph codes that are optimal for source/channel coding and binning.
IEEE Trans. Information Theory, 55(3):1061--1079. March 2009.
Full Text (PDF)
Preliminary versions:
Department of Statistics, Technical Report 730, April 2007.
M. J. Wainwright and E. Martinian, Low-density constructions can
achieve the Wyner-Ziv and Gelfand-Pinsker bounds.
International Symposium on Information Theory, Seattle, WA. July 2006.
Full Text (151K pdf)
E. Martinian and M. J. Wainwright, Low-density
codes achieve the rate-distortion bound. Data Compression Conference, Snowbird, UT. March 2006.
Full Text (191K pdf)
E. Martinian and M. J. Wainwright, Analysis of
LDGM and compound codes for lossy compression and binning.
Workshop on Information Theory and its
Applications, San Diego, CA. February 2006.
Full Text (185K pdf)
C. Daskalakis, A. G. Dimakis, R. Karp and
M. J. Wainwright. Probabilistic analysis of
linear programming decoding. IEEE. Trans. Information Theory,
Vol. 54(8): pp. 3565--3578, August 2008.
Full text (PDF)
Preliminary version: Extended abstract in
SIAM Symposium on Discrete
Algorithms, New Orleans, LA. January 2007.
A. D. G. Dimakis, M. J. Wainwright, M.J., and K. Ramchandran,
Lower bounds on the rate-distortion function of LDGM codes.
Information Theory Workshop (ITW), September 2007, pp. 650 - 655.
Full Text (PDF)
M. J. Wainwright,
Sparse graph codes for side information and binning,
IEEE Signal Processing Magazine: 24(5): 47--57, September 2007.
Full Text (PDF)
L. Dolecek, Z. Zhang, M. J. Wainwright, V. Anantharam, and B.
Nikolic, Evaluation of the low frame error rate performance of LDPC
codes using importance sampling, IEEE Information Theory Workshop,
Lake Tahoe CA, September 2007, pp. 202 - 207.
Full Text (PDF)
L. Dolecek, Z. Zhang, V. Anantharam, M. J. Wainwright, and B.
Nikolic, Analysis of Absorbing Sets for Array-Based LDPC Codes,
IEEE International Conference on Communications (ICC), Glasgow,
United Kingdom, June 2007, pp. 6261-6268.
Z. Zhang, L. Dolecek, V. Anantharam, M. J. Wainwright, and B. Nikolic, Quantization Effects in Low-Density Parity-Check Decoders,
IEEE International Conference on Communications (ICC), Glasgow,
United Kingdom, June 2007, pp. 6231-6237.
Full Text (PDF)
A. Dimakis, B. Godfrey, M. J. Wainwright and K. Ramchandran,
Network Coding for Distributed Storage Systems
INFOCOM 2007, Anchorage, Alaska. May 2007.
Full Text (PDF)
Z. Zhang, L. Dolecek, B. Nikolic, V. Anantharam, and
M. J. Wainwright, Investigation of error floors of structured
low-density parity-check codes by hardware emulation.
Proceedings of IEEE Globecom, San Francisco, CA, November 2006.
Full Text (1.2M pdf)
M. J. Wainwright and E. Maneva, Lossy source coding via
message-passing and decimation over generalized codewords of LDGM codes.
Presented at the International Symposium on Information Theory, Adelaide, Australia.
September, 2005.
Full Text (1.7M ps) /
Full Text (304K pdf)
J. Feldman, T. Malkin, R. Servedio, C. Stein
and M. J. Wainwright,
LP Decoding Corrects a Constant Fraction of Errors.
IEEE Trans. Information Theory, (53):82--89.
January, 2007.
Full Text (280K pdf)
Preliminary versions:
CORC Technical Report TR-2003-08, Industrial Engineering and Operations
Research, Columbia University. December 2003.
Presented at International Symposium on Information Theory, Chicago, IL. July,
2004.
J. Feldman, M. J. Wainwright and D. R. Karger. (2005)
Using linear programming to decode binary linear codes.
IEEE Transactions on Information Theory, (51):954-972.
Full Text (531K pdf) /
Link to paper on IEEExplore
Preliminary versions:
J. Feldman, D. Karger and M. J. Wainwright,
LP Decoding
Invited Paper; Allerton Conference on Communication, Control,
and Computing; October 1--3, 2003; Urbana-Champaign, IL.
Full Text (173K pdf)
J. Feldman, D. Karger and M. Wainwright,
Using linear programming to decode LDPC codes.
Conference on Information Sciences and
Systems, Baltimore, March 2003.
Full Text (173K pdf)
J. Feldman, D. Karger and M. Wainwright,
Linear programming-based decoding of turbo-like codes and its relation
to iterative approaches.
Presented at the Allerton Conference on Communication, Control,
and Computing; October 2--4, 2002; Urbana-Champaign, IL.
Full Text (352K ps) /
Full Text (352K pdf)
J. Portilla, V. Strela, M. J. Wainwright and E.P. Simoncelli.
Image denoising using Gaussian scale mixtures in the wavelet
domain. IEEE Transactions on Image Processing, November
2003. Vol. 12, pp. 1338-1351. IEEE Signal Processing Society, Best Paper Award (2008)
Local PDF file /
Link to IEEExplore
Preliminary version:
J. Portilla, V. Strela, M. J. Wainwright and E.P. Simoncelli.
Adaptive Wiener denoising using a Gaussian scale mixture model in
the wavelet domain.
Proceedings of the 8th International Conference on Image Processing.
October, 2001; Greece.
M. J. Wainwright,
E. P. Simoncelli and A. S. Willsky. Random cascades on wavelet trees and their use in analyzing and modeling natural images.
Applied Computational and Harmonic Analysis (2001), vol. 11, pages
89--123.
Full Text (822K pdf)
Preliminary versions:
M. J. Wainwright,
E. P. Simoncelli and A. S. Willsky. Random cascades on
wavelet trees and their use in analyzing and modeling natural images.
Invited Paper; Published in Proceedings of the 45th Annual Meeting of the SPIE.
San Diego, CA; July 30 -- August 4, 2000.
M. J. Wainwright, E. P. Simoncelli and A. S. Willsky.
Random cascades of Gaussian scale mixtures and their use in modeling natural images with application to denoising.
Proceedings of the 7th International Conference on Image Processing.
Vancouver, BC, Canada. 10-13 September 2000.
M. J. Wainwright and
E. P. Simoncelli. Scale Mixtures of Gaussians and the
Statistics of Natural Images. Conference on Neural
Information Processing Systems (NIPS). Denver, CO. Nov 29-Dec 2,
1999; pages 855--861.
Full Text (1.8M, pdf)
M. J. Wainwright, O. Schwartz, and E. P. Simoncelli, "Natural
image statistics and divisive normalization: Modeling nonlinearities
and adaptation in cortical neurons", Chapter 10, pages 203--222;
Statistical Theories of the Brain, Eds. P. Rao, B. Olshausen and
M. Lewicki, MIT Press 2002.
Full Text (137K, pdf)
M. J. Wainwright, "Visual adaptation as optimal information transmission",
Vision Research , 39:3960--3974, 1999.
Full Text (245K, pdf)
M. J. Wainwright, "Stochastic Processes on Graphs: Geometric and Variational
Approaches", Ph.D. Thesis, Department of EECS, Massachusetts Institute of
Technology, 2002.
Full Text (3.9M, pdf)