Fetching the paper…
Reading the bibliography…
Consider the following class of learning schemes: $$\hat{\boldsymbol{\beta}} := \arg\min_{\boldsymbol{\beta}}\;\sum_{j=1}^n \ell(\boldsymbol{x}_j^\top\boldsymbol{\beta}; y_j) + \lambda R(\boldsymbol{\beta}),\qquad\qquad (1) $$ where $\boldsymbol{x}_i \in \mathbb{R}^p$ and $y_i \in \mathbb{R}$ denote the $i^{\text{th}}$ feature and response variable respectively.
Das asymptotische verteilungsgestez der eigenwert linearer partieller differentialgleichungen (mit einer anwendung auf der theorie der hohlraumstrahlung)
L Weyl · 1912
Earlier work this paper cites.
Inverting modified matrices
Max A Woodbury · 1950
Earlier work this paper cites.
Symmetric gauge functions and unitarily invariant norms
L Mirsky · 1960
Earlier work this paper cites.
Convex analysis
R. Tyrrell Rockafellar · 1970
Earlier work this paper cites.
Robust regression: asymptotics, conjectures and monte carlo
Peter J Huber · 1973
Earlier work this paper cites.
The relationship between variable selection and data agumentation and a method for prediction
David M Allen · 1974
Earlier work this paper cites.
Cross-validatory choice and assessment of statistical predictions
Mervyn Stone · 1974
Earlier work this paper cites.
Coronary risk factor screening in three rural communities. the coris baseline study
JE Rossouw, JP Du Plessis, AJ Benadé, PC Jordaan, JP Kotze, PL Jooste, and JJ Ferreira · 1983
Earlier work this paper cites.
Automatic smoothing of regression functions in generalized linear models
Finbarr O’sullivan, Brian S Yandell, and William J Raynor Jr · 1986
Earlier work this paper cites.
Updating the inverse of a matrix
William W Hager · 1989
Earlier work this paper cites.
Ridge estimators in logistic regression
Saskia Le Cessie and Johannes C Van Houwelingen · 1992
Earlier work this paper cites.
Support-vector networks
Corinna Cortes and Vladimir Vapnik · 1995
Earlier work this paper cites.
The convex analysis of unitarily invariant matrix functions
Adrian S Lewis · 1995
Earlier work this paper cites.
Regression shrinkage and selection via the lasso
Robert Tibshirani · 1996
Earlier work this paper cites.
Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays
Uri Alon, Naama Barkai, Daniel A Notterman, Kurt Gish, Suzanne Ybarra, Daniel Mack, and Arnold J Levine · 1999
Earlier work this paper cites.
Gaussian processes and svm: Mean field results and leave-one-out
Manfred Opper and Ole Winther · 2000
Earlier work this paper cites.
Convex optimization
Stephen Boyd and Lieven Vandenberghe · 2004
Cited alongside, same era.
The estimation of prediction error: covariance penalties and cross-validation
Bradley Efron · 2004
Cited alongside, same era.
Neighborliness of randomly projected simplices in high dimensions
David L Donoho and Jared Tanner · 2005
Cited alongside, same era.
Result analysis of the nips 2003 feature selection challenge
Isabelle Guyon, Steve Gunn, Asa Ben-Hur, and Gideon Dror · 2005
Cited alongside, same era.
Sparsity and smoothness via the fused lasso
Robert Tibshirani, Michael Saunders, Saharon Rosset, Ji Zhu, and Keith Knight · 2005
Cited alongside, same era.
On the “degrees of freedom” of the lasso
Hui Zou, Trevor Hastie, Robert Tibshirani, et al · 2007
Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
Later among the works it cites.
The solution path of the generalized lasso
Ryan J. Tibshirani and Jonathan Taylor · 2011
Later among the works it cites.
Degrees of freedom in lasso problems
Ryan J Tibshirani, Jonathan Taylor, et al · 2012
Later among the works it cites.
Estimating lasso risk and noise level
Mohsen Bayati, Murat A Erdogdu, and Andrea Montanari · 2013
Later among the works it cites.
Unbiased risk estimates for singular value thresholding and spectral estimators
Emmanuel J Candes, Carlos A Sing-Long, and Joshua D Trzasko · 2013
Later among the works it cites.
The degrees of freedom of the lasso for general design matrix
Charles Dossal, Maher Kachour, MJ Fadili, Gabriel Peyré, and Christophe Chesneau · 2013
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Efficient approximate leave-one-out cross-validation for kernel logistic regression
Gavin C Cawley and Nicola LC Talbot · 2008
Cited alongside, same era.
Message-passing algorithms for compressed sensing
David L Donoho, Arian Maleki, and Andrea Montanari · 2009
Cited alongside, same era.
Elements of Statistical Learning
Trevor Hastie, Robert Tishirani, and Jerome Friedman · 2009
Cited alongside, same era.
Elements of Statistical Learning
Trevor Hastie, Robert Tishirani, and Jerome Friedman · 2009
Cited alongside, same era.
l 1 l_{1} trend filtering
Seung-Jean Kim, Kwangmoo Koh, Stephen Boyd, and Dimitry Gorinevsky · 2009
Cited alongside, same era.
Templates for convex cone problems with applications to sparse signal recovery
Stephen R. Becker, Emmanuel J. Candès, and Michael C. Grant · 2011
Cited alongside, same era.
Later among the works it cites.
Efficient approximate k-fold and leave-one-out cross-validation for ridge regression
Rosa J Meijer and Jelle J Goeman · 2013
Later among the works it cites.
Glmnet for matlab 2013
Junyang Qian, T Hastie, J Friedman, R Tibshirani, and N Simon · 2013
Later among the works it cites.
Living on the edge: Phase transitions in convex programs with random data
Dennis Amelunxen, Martin Lotz, Michael B McCoy, and Joel A Tropp · 2014
Later among the works it cites.
CVX: Matlab software for disciplined convex programming, version 2.1
Michael Grant and Stephen Boyd · 2014
Later among the works it cites.
Cross validation in lasso and its acceleration
Tomoyuki Obuchi and Yoshiyuki Kabashima · 2016
Later among the works it cites.
On optimal generalizability in parametric learning
Ahmad Beirami, Meisam Razaviyayn, Shahin Shahrampour, and Vahid Tarokh · 2017
Later among the works it cites.
Consistent parameter estimation for lasso and approximate message passing
Ali Mousavi, Arian Maleki, Richard G Baraniuk, et al · 2017
Later among the works it cites.
The degrees of freedom of partly smooth regularizers
Samuel Vaiter, Charles Deledalle, Jalal Fadili, Gabriel Peyré, and Charles Dossal · 2017
Later among the works it cites.
A scalable estimate of the extra-sample prediction error via approximate leave-one-out
Kamiar Rad and Arian Maleki · 2018
Closest in time.