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The distribution of the Lasso: Uniform control over sparse balls and
  adaptive parameter tuning

The distribution of the Lasso: Uniform control over sparse balls and adaptive parameter tuning

3 November 2018
Léo Miolane
Andrea Montanari
ArXiv (abs)PDFHTML

Papers citing "The distribution of the Lasso: Uniform control over sparse balls and adaptive parameter tuning"

35 / 35 papers shown
Title
Optimal Implicit Bias in Linear Regression
Optimal Implicit Bias in Linear Regression
K. N. Varma
Babak Hassibi
11
0
0
20 Jun 2025
Simultaneous analysis of approximate leave-one-out cross-validation and mean-field inference
Pierre C Bellec
112
0
0
05 Jan 2025
Derivatives and residual distribution of regularized M-estimators with application to adaptive tuning
Derivatives and residual distribution of regularized M-estimators with application to adaptive tuning
Pierre C. Bellec
Yi Shen
124
13
0
03 Jan 2025
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs
Kasimir Tanner
Matteo Vilucchio
Bruno Loureiro
Florent Krzakala
AAML
97
1
0
31 Dec 2024
Understanding Optimal Feature Transfer via a Fine-Grained Bias-Variance Analysis
Understanding Optimal Feature Transfer via a Fine-Grained Bias-Variance Analysis
Yufan Li
Subhabrata Sen
Ben Adlam
MLT
175
1
0
18 Apr 2024
Regularized Linear Regression for Binary Classification
Regularized Linear Regression for Binary Classification
D. Akhtiamov
Reza Ghane
Babak Hassibi
NoLa
51
3
0
03 Nov 2023
High-dimensional Contextual Bandit Problem without Sparsity
High-dimensional Contextual Bandit Problem without Sparsity
Junpei Komiyama
Masaaki Imaizumi
78
2
0
19 Jun 2023
Approximate message passing from random initialization with applications
  to $\mathbb{Z}_{2}$ synchronization
Approximate message passing from random initialization with applications to Z2\mathbb{Z}_{2}Z2​ synchronization
Gen Li
Wei Fan
Yuting Wei
95
12
0
07 Feb 2023
Gaussian random projections of convex cones: approximate kinematic
  formulae and applications
Gaussian random projections of convex cones: approximate kinematic formulae and applications
Q. Han
Hua Ren
76
3
0
11 Dec 2022
Sudakov-Fernique post-AMP, and a new proof of the local convexity of the
  TAP free energy
Sudakov-Fernique post-AMP, and a new proof of the local convexity of the TAP free energy
Michael Celentano
94
21
0
19 Aug 2022
Exact spectral norm error of sample covariance
Exact spectral norm error of sample covariance
Q. Han
70
8
0
27 Jul 2022
Algorithmic Gaussianization through Sketching: Converting Data into
  Sub-gaussian Random Designs
Algorithmic Gaussianization through Sketching: Converting Data into Sub-gaussian Random Designs
Michal Derezinski
81
5
0
21 Jun 2022
Overparametrized linear dimensionality reductions: From projection pursuit to two-layer neural networks
Overparametrized linear dimensionality reductions: From projection pursuit to two-layer neural networks
Andrea Montanari
Kangjie Zhou
82
2
0
14 Jun 2022
Noisy linear inverse problems under convex constraints: Exact risk
  asymptotics in high dimensions
Noisy linear inverse problems under convex constraints: Exact risk asymptotics in high dimensions
Q. Han
65
3
0
20 Jan 2022
Comparing Classes of Estimators: When does Gradient Descent Beat Ridge
  Regression in Linear Models?
Comparing Classes of Estimators: When does Gradient Descent Beat Ridge Regression in Linear Models?
Dominic Richards
Yan Sun
Patrick Rebeschini
68
3
0
26 Aug 2021
Asymptotic normality of robust $M$-estimators with convex penalty
Asymptotic normality of robust MMM-estimators with convex penalty
Pierre C. Bellec
Yiwei Shen
Cun-Hui Zhang
43
12
0
08 Jul 2021
Local convexity of the TAP free energy and AMP convergence for
  Z2-synchronization
Local convexity of the TAP free energy and AMP convergence for Z2-synchronization
Michael Celentano
Z. Fan
Song Mei
FedML
88
23
0
21 Jun 2021
Label-Imbalanced and Group-Sensitive Classification under
  Overparameterization
Label-Imbalanced and Group-Sensitive Classification under Overparameterization
Ganesh Ramachandra Kini
Orestis Paraskevas
Samet Oymak
Christos Thrampoulidis
129
96
0
02 Mar 2021
Learning curves of generic features maps for realistic datasets with a
  teacher-student model
Learning curves of generic features maps for realistic datasets with a teacher-student model
Bruno Loureiro
Cédric Gerbelot
Hugo Cui
Sebastian Goldt
Florent Krzakala
M. Mézard
Lenka Zdeborová
116
140
0
16 Feb 2021
Provable Benefits of Overparameterization in Model Compression: From
  Double Descent to Pruning Neural Networks
Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks
Xiangyu Chang
Yingcong Li
Samet Oymak
Christos Thrampoulidis
86
51
0
16 Dec 2020
Theoretical Insights Into Multiclass Classification: A High-dimensional
  Asymptotic View
Theoretical Insights Into Multiclass Classification: A High-dimensional Asymptotic View
Christos Thrampoulidis
Samet Oymak
Mahdi Soltanolkotabi
73
43
0
16 Nov 2020
Precise Statistical Analysis of Classification Accuracies for
  Adversarial Training
Precise Statistical Analysis of Classification Accuracies for Adversarial Training
Adel Javanmard
Mahdi Soltanolkotabi
AAML
105
63
0
21 Oct 2020
Out-of-sample error estimate for robust M-estimators with convex penalty
Out-of-sample error estimate for robust M-estimators with convex penalty
Pierre C. Bellec
129
17
0
26 Aug 2020
The Lasso with general Gaussian designs with applications to hypothesis
  testing
The Lasso with general Gaussian designs with applications to hypothesis testing
Michael Celentano
Andrea Montanari
Yuting Wei
127
64
0
27 Jul 2020
Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in
  High Dimensions
Fundamental Limits of Ridge-Regularized Empirical Risk Minimization in High Dimensions
Hossein Taheri
Ramtin Pedarsani
Christos Thrampoulidis
84
29
0
16 Jun 2020
Uncertainty quantification for nonconvex tensor completion: Confidence
  intervals, heteroscedasticity and optimality
Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality
Changxiao Cai
H. Vincent Poor
Yuxin Chen
118
23
0
15 Jun 2020
Aggregated hold out for sparse linear regression with a robust loss
  function
Aggregated hold out for sparse linear regression with a robust loss function
G. Maillard
FedML
70
1
0
26 Feb 2020
Sharp Asymptotics and Optimal Performance for Inference in Binary Models
Sharp Asymptotics and Optimal Performance for Inference in Binary Models
Hossein Taheri
Ramtin Pedarsani
Christos Thrampoulidis
84
26
0
17 Feb 2020
De-biasing convex regularized estimators and interval estimation in
  linear models
De-biasing convex regularized estimators and interval estimation in linear models
Pierre C. Bellec
Cun-Hui Zhang
128
20
0
26 Dec 2019
The Impact of Regularization on High-dimensional Logistic Regression
The Impact of Regularization on High-dimensional Logistic Regression
Fariborz Salehi
Ehsan Abbasi
B. Hassibi
136
103
0
10 Jun 2019
Approximate Cross-Validation in High Dimensions with Guarantees
Approximate Cross-Validation in High Dimensions with Guarantees
William T. Stephenson
Tamara Broderick
45
2
0
31 May 2019
SLOPE for Sparse Linear Regression:Asymptotics and Optimal
  Regularization
SLOPE for Sparse Linear Regression:Asymptotics and Optimal Regularization
Hong Hu
Yue M. Lu
42
2
0
27 Mar 2019
Fundamental Barriers to High-Dimensional Regression with Convex
  Penalties
Fundamental Barriers to High-Dimensional Regression with Convex Penalties
Michael Celentano
Andrea Montanari
96
48
0
25 Mar 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation
Surprises in High-Dimensional Ridgeless Least Squares Interpolation
Trevor Hastie
Andrea Montanari
Saharon Rosset
Robert Tibshirani
288
747
0
19 Mar 2019
On cross-validated Lasso in high dimensions
On cross-validated Lasso in high dimensions
Denis Chetverikov
Z. Liao
Victor Chernozhukov
97
81
0
07 May 2016
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