Fetching the paper…
Reading the bibliography…
Consider estimating an unknown, but structured, signal $x_0\in R^n$ from $m$ measurement $y_i=g_i(a_i^Tx_0)$, where the $a_i$'s are the rows of a known measurement matrix $A$, and, $g$ is a (potentially unknown) nonlinear and random link-function.
The identification of a particular nonlinear time series system
David R. Brillinger · 1977
Earlier work this paper cites.
A generalized linear model with” gaussian” regressor variables
David R Brillinger · 1982
Earlier work this paper cites.
Some inequalities for gaussian processes and applications
Yehoram Gordon · 1985
Earlier work this paper cites.
Regression analysis under link violation
Ker-Chau Li and Naihua Duan · 1989
Earlier work this paper cites.
Semiparametric least squares (sls) and weighted sls estimation of single-index models
Hidehiko Ichimura · 1993
Earlier work this paper cites.
Minimax risk overl p-balls forl p-error
David L Donoho and Iain M Johnstone · 1994
Earlier work this paper cites.
Large sample estimation and hypothesis testing
Whitney K Newey and Daniel McFadden · 1994
Earlier work this paper cites.
Regression shrinkage and selection via the lasso
Robert Tibshirani · 1996
Earlier work this paper cites.
Convex analysis
R Tyrell Rockafellar · 1997
Earlier work this paper cites.
Sparsity and smoothness via the fused lasso
Robert Tibshirani, Michael Saunders, Saharon Rosset, Ji Zhu, and Keith Knight · 2005
Earlier work this paper cites.
Model selection and estimation in regression with grouped variables
Ming Yuan and Yi Lin · 2006
Earlier work this paper cites.
Message-passing algorithms for compressed sensing
David L Donoho, Arian Maleki, and Andrea Montanari · 2009
Cited alongside, same era.
Structured sparsity-inducing norms through submodular functions
Francis R Bach · 2010
Cited alongside, same era.
Square-root lasso: pivotal recovery of sparse signals via conic programming
Alexandre Belloni, Victor Chernozhukov, and Lie Wang · 2011
Cited alongside, same era.
The noise-sensitivity phase transition in compressed sensing
David L Donoho, Arian Maleki, and Andrea Montanari · 2011
Cited alongside, same era.
The lasso risk for gaussian matrices
Mohsen Bayati and Andrea Montanari · 2012
Cited alongside, same era.
The convex geometry of linear inverse problems
Venkat Chandrasekaran, Benjamin Recht, Pablo A Parrilo, and Alan S Willsky · 2012
Cited alongside, same era.
The squared-error of generalized lasso: A precise analysis
Samet Oymak, Christos Thrampoulidis, and Babak Hassibi · 2013
Later among the works it cites.
A framework to characterize performance of lasso algorithms
Mihailo Stojnic · 2013
Later among the works it cites.
Maximin analysis of message passing algorithms for recovering block sparse signals
Armeen Taeb, Arian Maleki, Christoph Studer, and Richard Baraniuk · 2013
Later among the works it cites.
A totally unimodular view of structured sparsity
Marwa El Halabi and Volkan Cevher · 2014
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Living on the edge: A geometric theory of phase transitions in convex optimization
Dennis Amelunxen, Martin Lotz, Michael B McCoy, and Joel A Tropp · 2013
Cited alongside, same era.
Accurate prediction of phase transitions in compressed sensing via a connection to minimax denoising
David L Donoho, Lain Johnstone, and Andrea Montanari · 2013
Cited alongside, same era.
A note on least squares sensitivity in single-index model estimation and the benefits of response transformations
Alexandra L Garnham, Luke A Prendergast, et al · 2013
Cited alongside, same era.
Asymptotic analysis of complex lasso via complex approximate message passing (camp)
Arian Maleki, Laura Anitori, Zai Yang, and Richard G Baraniuk · 2013
Cited alongside, same era.
Yaniv Plan, Roman Vershynin, and Elena Yudovina · 2014
Later among the works it cites.
A tight version of the gaussian min-max theorem in the presence of convexity
Christos Thrampoulidis, Samet Oymak, and Babak Hassibi · 2014
Later among the works it cites.
The generalized lasso with non-linear observations
Yaniv Plan and Roman Vershynin · 2015
Closest in time.
Regularized linear regression: A precise analysis of the estimation error
Christos Thrampoulidis, Samet Oymak, and Babak Hassibi · 2015
Closest in time.
Precise error analysis of the lasso
Christos Thrampoulidis, Ashkan Panahi, Daniel Guo, and Babak Hassibi · 2015
Closest in time.
Asymptotically exact error analysis for the generalized ℓ 2 2 \ell_{2}^{2} -lasso
Christos Thrampoulidis, Ashkan Panahi, and Babak Hassibi · 2015
Closest in time.