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1111.0653
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Degrees of freedom in lasso problems
2 November 2011
Robert Tibshirani
Jonathan E. Taylor
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Papers citing
"Degrees of freedom in lasso problems"
50 / 105 papers shown
A Hierarchical Variational Graph Fused Lasso for Recovering Relative Rates in Spatial Compositional Data
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Ed Reznik
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Wesley Tansey
136
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25 Sep 2025
Convergence and Generalization of Anti-Regularization for Parametric Models
Dongseok Kim
Wonjun Jeong
Gisung Oh
297
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24 Aug 2025
Tuning parameter selection in econometrics
Denis Chetverikov
321
4
0
05 May 2024
Robust Elastic Net Estimators for High Dimensional Generalized Linear Models
Marina Valdora
Claudio Agostinelli
OOD
251
0
0
07 Dec 2023
Corrected generalized cross-validation for finite ensembles of penalized estimators
Pierre C. Bellec
Jin-Hong Du
Takuya Koriyama
Pratik Patil
Kai Tan
447
7
0
02 Oct 2023
Correcting for heterogeneity in real-time epidemiological indicators
Aaron M. Rumack
Roni Rosenfeld
F. W. Townes
117
1
0
28 Sep 2023
Degrees of Freedom: Search Cost and Self-consistency
Journal of Computational And Graphical Statistics (JCGS), 2023
Lijun Wang
Hongyu Zhao
Xiaodan Fan
142
0
0
25 Aug 2023
Information criteria for structured parameter selection in high dimensional tree and graph models
M. Jansen
185
5
0
24 Jun 2023
FAStEN: an efficient adaptive method for feature selection and estimation in high-dimensional functional regressions
Journal of Computational And Graphical Statistics (JCGS), 2023
Tobia Boschi
Lorenzo Testa
Francesca Chiaromonte
M. Reimherr
359
8
0
26 Mar 2023
Average case analysis of Lasso under ultra-sparse conditions
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Koki Okajima
Xiangming Meng
Takashi Takahashi
Y. Kabashima
254
7
0
25 Feb 2023
The Voronoigram: Minimax Estimation of Bounded Variation Functions From Scattered Data
Addison J. Hu
Alden Green
Robert Tibshirani
356
4
0
30 Dec 2022
Tractable Evaluation of Stein's Unbiased Risk Estimate with Convex Regularizers
IEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2022
Parth Nobel
Emmanuel Candès
Stephen P. Boyd
ELM
LLMSV
303
8
0
11 Nov 2022
Dynamics-informed deconvolutional neural networks for super-resolution identification of regime changes in epidemiological time series
medRxiv (medRxiv), 2022
J. Vilar
L. Saiz
89
9
0
16 Sep 2022
Variance estimation in graphs with the fused lasso
Journal of machine learning research (JMLR), 2022
Oscar Hernan Madrid Padilla
525
7
0
26 Jul 2022
Observable adjustments in single-index models for regularized M-estimators
Annals of Statistics (Ann. Stat.), 2022
Pierre C. Bellec
349
13
0
14 Apr 2022
Robust signal dimension estimation via SURE
Statistical Papers (SP), 2022
Joni Virta
Niko Lietzén
Henri Nyberg
149
1
0
30 Mar 2022
Two Gaussian regularization methods for time-varying networks
Journal of Agricultural Biological and Environmental Statistics (JABES), 2022
Jie Jian
Peijun Sang
Mu Zhu
290
1
0
14 Feb 2022
Statistical Learning for Individualized Asset Allocation
Journal of the American Statistical Association (JASA), 2022
Yi Ding
Yingying Li
Rui Song
292
0
0
20 Jan 2022
Multivariate Trend Filtering for Lattice Data
Annals of Statistics (Ann. Stat.), 2021
Veeranjaneyulu Sadhanala
Yu Wang
Addison J. Hu
Robert Tibshirani
322
7
0
29 Dec 2021
Unbiased Risk Estimation in the Normal Means Problem via Coupled Bootstrap Techniques
Natalia L. Oliveira
Jing Lei
Robert Tibshirani
305
11
0
17 Nov 2021
Denoising and change point localisation in piecewise-constant high-dimensional regression coefficients
Fan Wang
Oscar Hernan Madrid Padilla
Yi Yu
Alessandro Rinaldo
281
5
0
27 Oct 2021
The R package sentometrics to compute, aggregate and predict with textual sentiment
Journal of Statistical Software (JSS), 2020
David Ardia
Keven Bluteau
S. Borms
Kris Boudt
100
24
0
20 Oct 2021
Quantile Regression by Dyadic CART
Oscar Hernan Madrid Padilla
S. Chatterjee
204
1
0
16 Oct 2021
yaglm: a Python package for fitting and tuning generalized linear models that supports structured, adaptive and non-convex penalties
Iain Carmichael
T. Keefe
Naomi Giertych
Jonathan P. Williams
205
2
0
11 Oct 2021
Efficient Multidimensional Functional Data Analysis Using Marginal Product Basis Systems
Journal of Computational And Graphical Statistics (JCGS), 2021
W. Consagra
A. Venkataraman
Xing Qiu
423
3
0
30 Jul 2021
Lattice partition recovery with dyadic CART
Neural Information Processing Systems (NeurIPS), 2021
Oscar Hernan Madrid Padilla
Yi Yu
Alessandro Rinaldo
394
7
0
27 May 2021
Bridging between soft and hard thresholding by scaling
K. Hagiwara
152
6
0
20 Apr 2021
Modelling Heterogeneity Using Bayesian Structured Sparsity
Max Goplerud
CML
273
4
0
29 Mar 2021
An Optimal Reduction of TV-Denoising to Adaptive Online Learning
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Dheeraj Baby
Xuandong Zhao
Yu Wang
273
12
0
23 Jan 2021
Non-parametric Quantile Regression via the K-NN Fused Lasso
Journal of machine learning research (JMLR), 2020
Steven Siwei Ye
Oscar Hernan Madrid Padilla
554
14
0
03 Dec 2020
High dimensional asymptotics of likelihood ratio tests in the Gaussian sequence model under convex constraints
Q. Han
B. Sen
Yandi Shen
518
3
0
07 Oct 2020
Out-of-sample error estimate for robust M-estimators with convex penalty
Pierre C. Bellec
641
18
0
26 Aug 2020
Risk Bounds for Quantile Trend Filtering
Biometrika (Biometrika), 2020
Oscar Hernan Madrid Padilla
S. Chatterjee
515
24
0
15 Jul 2020
Revisiting minimum description length complexity in overparameterized models
Raaz Dwivedi
Chandan Singh
Bin Yu
Martin J. Wainwright
543
5
0
17 Jun 2020
An Efficient Semi-smooth Newton Augmented Lagrangian Method for Elastic Net
Tobia Boschi
M. Reimherr
Francesca Chiaromonte
219
3
0
06 Jun 2020
Automated data-driven selection of the hyperparameters for Total-Variation based texture segmentation
Journal of Mathematical Imaging and Vision (JMIV), 2020
Barbara Pascal
Samuel Vaiter
N. Pustelnik
P. Abry
383
21
0
20 Apr 2020
The Geometry of Uniqueness, Sparsity and Clustering in Penalized Estimation
Journal of machine learning research (JMLR), 2020
U. Schneider
P. Tardivel
529
24
0
20 Apr 2020
Divided Differences, Falling Factorials, and Discrete Splines: Another Look at Trend Filtering and Related Problems
Robert Tibshirani
319
22
0
09 Mar 2020
Aggregated hold out for sparse linear regression with a robust loss function
Electronic Journal of Statistics (EJS), 2020
G. Maillard
FedML
341
1
0
26 Feb 2020
Degrees of freedom for off-the-grid sparse estimation
Bernoulli (Bernoulli), 2019
C. Poon
Gabriel Peyré
302
3
0
08 Nov 2019
Harmonization of diffusion MRI datasets with adaptive dictionary learning
bioRxiv (bioRxiv), 2019
Samuel St-Jean
M. Viergever
A. Leemans
MedIm
486
19
0
01 Oct 2019
Computing the degrees of freedom of rank-regularized estimators and cousins
Electronic Journal of Statistics (EJS), 2019
Rahul Mazumder
Haolei Weng
147
4
0
23 Sep 2019
De-Biasing The Lasso With Degrees-of-Freedom Adjustment
Pierre C. Bellec
Cun-Hui Zhang
448
31
0
24 Feb 2019
Second order Stein: SURE for SURE and other applications in high-dimensional inference
Pierre C. Bellec
Cun-Hui Zhang
458
36
0
09 Nov 2018
The distribution of the Lasso: Uniform control over sparse balls and adaptive parameter tuning
Léo Miolane
Andrea Montanari
328
99
0
03 Nov 2018
Estimation of the Spatial Weighting Matrix for Spatiotemporal Data under the Presence of Structural Breaks
Philipp Otto
R. Steinert
213
12
0
16 Oct 2018
Approximate Leave-One-Out for High-Dimensional Non-Differentiable Learning Problems
Shuaiwen Wang
Wenda Zhou
A. Maleki
Haihao Lu
Vahab Mirrokni
309
14
0
04 Oct 2018
Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions
International Conference on Machine Learning (ICML), 2018
Shuaiwen Wang
Wenda Zhou
Haihao Lu
A. Maleki
Vahab Mirrokni
262
36
0
07 Jul 2018
The Well Tempered Lasso
Yuanzhi Li
Y. Singer
185
7
0
08 Jun 2018
The Generalized Lasso Problem and Uniqueness
Alnur Ali
Robert Tibshirani
258
48
0
20 May 2018
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