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We consider the problem of robustifying high-dimensional structured estimation.
Ising, E. (1925), “Beitrag zur Theorie der Ferromagnetismus,”
1925
Earlier work this paper cites.
Hassner, M. and Sklansky, J. (1978), “Markov Random Field Models of Digitized Image Texture,” in
1978
Earlier work this paper cites.
Woods, J. (1978), “Markov Image Modeling,”
1978
Earlier work this paper cites.
Ripley, B. D. (1981),
1981
Earlier work this paper cites.
Cross, G. and Jain, A. (1983), “Markov Random Field Texture Models,”
1983
Earlier work this paper cites.
Rousseeuw, P. J. (1984), “Least median of squares regression,”
1984
Earlier work this paper cites.
Lauritzen, S. (1996),
1996
Earlier work this paper cites.
Stratton, H., Zhou, J., Reed, S., and Stone, D. (1996), “The Mating-Specific Galpha Protein of Saccharomyces cerevisiae Downregulates the Mating Signal by a Mechanism That Is Dependent on Pheromone and Independent of Gbetagamma Sequestration,”
1996
Earlier work this paper cites.
Tibshirani, R. (1996), “Regression shrinkage and selection via the lasso,”
1996
Earlier work this paper cites.
Manning, C. D. and Schutze, H. (1999),
1999
Earlier work this paper cites.
Golub, G. and Pereyra, V. (2003), “Separable nonlinear least squares: the variable projection method and its applications,”
2003
Earlier work this paper cites.
Boyd, S. and Vandenberghe, L. (2004),
2004
Earlier work this paper cites.
Nesterov, Y. (2004),
2004
Earlier work this paper cites.
Brem, R. B. and Kruglyak, L. (2005), “The landscape of genetic complexity across 5,700 gene expression traits in yeast,”
2005
Earlier work this paper cites.
Brem, R. B., Storey, J. D., Whittle, J., and Kruglyak, L. (2005), “Genetic interactions between polymorphisms that affect gene expression in yeast.”
2005
Earlier work this paper cites.
Candès, E., Romberg, J., and Tao, T. (2006), “Stable signal recovery from incomplete and inaccurate measurements,”
2006
Earlier work this paper cites.
Meinshausen, N. and Bühlmann, P. (2006), “High-dimensional graphs and variable selection with the Lasso,”
2006
Cited alongside, same era.
Friedman, J., Hastie, T., and Tibshirani, R. (2007), “Sparse inverse covariance estimation with the graphical Lasso,”
2007
Cited alongside, same era.
Wang, H., Li, G., and Jiang, G. (2007), “Robust regression shrinkage and consistent variable selection through the LAD-lasso,”
2007
Cited alongside, same era.
Yuan, M. and Lin, Y. (2007), “Model selection and estimation in the Gaussian graphical model,”
2007
Cited alongside, same era.
Bannerjee, O., , Ghaoui, L. E., and d’Aspremont, A. (2008), “Model selection through sparse maximum likelihood estimation for multivariate Gaussian or binary data,”
2008
Cited alongside, same era.
Negahban, S., Ravikumar, P., Wainwright, M. J., and Yu, B. (2012), “A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers,”
2012
Later among the works it cites.
Sun, H. and Li, H. (2012), “Robust Gaussian graphical modeling via l1 penalization,”
2012
Later among the works it cites.
Vershynin, R. (2012), “Introduction to the non-asymptotic analysis of random matrices,” in
2012
Later among the works it cites.
Yang, E., Ravikumar, P., Allen, G. I., and Liu, Z. (2012), “Graphical Models via Generalized Linear Models,” in
2012
Later among the works it cites.
Alfons, A., Croux, C., and Gelper, S. (2013), “Sparse least trimmed squares regression for analyzing high-dimensional large data sets,”
2013
Later among the works it cites.
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Bunea, F. (2008), “Honest variable selection in linear and logistic regression models via l1 and l1 + l2 penalization,”
2008
Cited alongside, same era.
Beck, A. and Teboulle, M. (2009), “A fast iterative shrinkage-thresholding algorithm for linear inverse problems,”
2009
Cited alongside, same era.
Rockafellar, R. T. and Wets, R. J.-B. (2009),
2009
Cited alongside, same era.
van de Geer, S. and Buhlmann, P. (2009), “On the conditions used to prove oracle results for the Lasso,”
2009
Cited alongside, same era.
Wainwright, M. J. (2009), “Sharp thresholds for high-dimensional and noisy sparsity recovery using
2009
Cited alongside, same era.
Raskutti, G., Wainwright, M. J., and Yu, B. (2010), “Restricted Eigenvalue Properties for Correlated Gaussian Designs,”
2010
Cited alongside, same era.
Recht, B., Fazel, M., and Parrilo, P. A. (2010), “Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization,”
2010
Cited alongside, same era.
Chen, Y., Caramanis, C., and Mannor, S. (2013), “Robust High Dimensional Sparse Regression and Matching Pursuit,”
2013
Later among the works it cites.
Loh, P.-L. and Wainwright, M. J. (2013), “Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima,” in
2013
Later among the works it cites.
Yang, E. and Ravikumar, P. (2013), “Dirty Statistical Models,” in
2013
Later among the works it cites.
Yang, E., Tewari, A., and Ravikumar, P. (2013), “On Robust Estimation of High Dimensional Generalized Linear Models,” in
2013
Later among the works it cites.
Kanehisa, M., Goto, S., Sato, Y., Kawashima, M., Furumichi, M., and Tanabe, M. (2014), “Data, information, knowledge and principle: back to metabolism in KEGG,”
2014
Later among the works it cites.
Oh, J. H. and Deasy, J. O. (2014), “Inference of radio-responsive gene regulatory networks using the graphical lasso algorithm,”
2014
Later among the works it cites.
Tibshirani, J. and Manning, C. D. (2014), “Robust Logistic Regression using Shift Parameters.” in
2014
Later among the works it cites.
Loh, P. and Wainwright, M. J. (2015), “Regularized M-estimators with Nonconvexity: Statistical and Algorithmic Theory for Local Optima,”
2015
Later among the works it cites.
Yang, E. and Lozano, A. C. (2015), “Robust Gaussian Graphical Modeling with the Trimmed Graphical Lasso,” in
2015
Later among the works it cites.
Tu, N., Aravkin, A., van Leeuwen, T., Lin, T., and Herrmann, F. J. (2016), “Source estimation with surface-related multiples—fast ambiguity-resolved seismic imaging,”
2016
Closest in time.
Nguyen, N. H. and Tran, T. D. (2013), “Robust Lasso with missing and grossly corrupted observations,”
2058
Closest in time.