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Generic Error Bounds for the Generalized Lasso with Sub-Exponential Data

Generic Error Bounds for the Generalized Lasso with Sub-Exponential Data

11 April 2020
Martin Genzel
Christian Kipp
ArXivPDFHTML

Papers citing "Generic Error Bounds for the Generalized Lasso with Sub-Exponential Data"

29 / 29 papers shown
Title
Sparsified Simultaneous Confidence Intervals for High-Dimensional Linear Models
Sparsified Simultaneous Confidence Intervals for High-Dimensional Linear Models
Xiaorui Zhu
Yi Qin
Peng Wang
41
0
0
14 Jul 2023
Sharp Concentration Results for Heavy-Tailed Distributions
Sharp Concentration Results for Heavy-Tailed Distributions
Milad Bakhshizadeh
A. Maleki
Víctor Pena
32
22
0
30 Mar 2020
Sub-Gaussian Matrices on Sets: Optimal Tail Dependence and Applications
Sub-Gaussian Matrices on Sets: Optimal Tail Dependence and Applications
Halyun Jeong
Xiaowei Li
Y. Plan
Özgür Yilmaz
50
18
0
28 Jan 2020
Quickly Finding the Best Linear Model in High Dimensions
Quickly Finding the Best Linear Model in High Dimensions
Yahya Sattar
Samet Oymak
49
8
0
03 Jul 2019
Fundamental Barriers to High-Dimensional Regression with Convex
  Penalties
Fundamental Barriers to High-Dimensional Regression with Convex Penalties
Michael Celentano
Andrea Montanari
60
46
0
25 Mar 2019
The Generalized Lasso for Sub-gaussian Measurements with Dithered
  Quantization
The Generalized Lasso for Sub-gaussian Measurements with Dithered Quantization
Christos Thrampoulidis
A. S. Rawat
MQ
50
30
0
18 Jul 2018
Structured Recovery with Heavy-tailed Measurements: A Thresholding
  Procedure and Optimal Rates
Structured Recovery with Heavy-tailed Measurements: A Thresholding Procedure and Optimal Rates
Xiaohan Wei
45
11
0
16 Apr 2018
Moving Beyond Sub-Gaussianity in High-Dimensional Statistics:
  Applications in Covariance Estimation and Linear Regression
Moving Beyond Sub-Gaussianity in High-Dimensional Statistics: Applications in Covariance Estimation and Linear Regression
Arun K. Kuchibhotla
Abhishek Chakrabortty
40
108
0
08 Apr 2018
Learning Compact Neural Networks with Regularization
Learning Compact Neural Networks with Regularization
Samet Oymak
MLT
66
39
0
05 Feb 2018
Lifting high-dimensional nonlinear models with Gaussian regressors
Lifting high-dimensional nonlinear models with Gaussian regressors
Christos Thrampoulidis
A. S. Rawat
41
8
0
11 Dec 2017
On Stein's Identity and Near-Optimal Estimation in High-dimensional
  Index Models
On Stein's Identity and Near-Optimal Estimation in High-dimensional Index Models
Zhuoran Yang
Krishnakumar Balasubramanian
Han Liu
20
15
0
26 Sep 2017
Convergence rates of least squares regression estimators with
  heavy-tailed errors
Convergence rates of least squares regression estimators with heavy-tailed errors
Q. Han
J. Wellner
41
45
0
07 Jun 2017
Fast and Reliable Parameter Estimation from Nonlinear Observations
Fast and Reliable Parameter Estimation from Nonlinear Observations
Samet Oymak
Mahdi Soltanolkotabi
130
25
0
23 Oct 2016
Structured signal recovery from non-linear and heavy-tailed measurements
Structured signal recovery from non-linear and heavy-tailed measurements
L. Goldstein
Stanislav Minsker
Xiaohan Wei
58
46
0
05 Sep 2016
Regularization and the small-ball method II: complexity dependent error
  rates
Regularization and the small-ball method II: complexity dependent error rates
Guillaume Lecué
S. Mendelson
45
39
0
27 Aug 2016
High-Dimensional Estimation of Structured Signals from Non-Linear
  Observations with General Convex Loss Functions
High-Dimensional Estimation of Structured Signals from Non-Linear Observations with General Convex Loss Functions
Martin Genzel
238
45
0
10 Feb 2016
Regularization and the small-ball method I: sparse recovery
Regularization and the small-ball method I: sparse recovery
Guillaume Lecué
S. Mendelson
41
93
0
21 Jan 2016
Sparse Nonlinear Regression: Parameter Estimation and Asymptotic
  Inference
Sparse Nonlinear Regression: Parameter Estimation and Asymptotic Inference
Zhuoran Yang
Zhaoran Wang
Han Liu
Yonina C. Eldar
Tong Zhang
66
43
0
14 Nov 2015
Sharp Time--Data Tradeoffs for Linear Inverse Problems
Sharp Time--Data Tradeoffs for Linear Inverse Problems
Samet Oymak
Benjamin Recht
Mahdi Soltanolkotabi
57
88
0
16 Jul 2015
The LASSO with Non-linear Measurements is Equivalent to One With Linear
  Measurements
The LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements
Christos Thrampoulidis
Ehsan Abbasi
B. Hassibi
61
116
0
06 Jun 2015
The generalized Lasso with non-linear observations
The generalized Lasso with non-linear observations
Y. Plan
Roman Vershynin
133
199
0
13 Feb 2015
Learning without Concentration for General Loss Functions
Learning without Concentration for General Loss Functions
S. Mendelson
109
65
0
13 Oct 2014
Convex recovery of a structured signal from independent random linear
  measurements
Convex recovery of a structured signal from independent random linear measurements
J. Tropp
66
176
0
05 May 2014
Randomized Sketches of Convex Programs with Sharp Guarantees
Randomized Sketches of Convex Programs with Sharp Guarantees
Mert Pilanci
Martin J. Wainwright
292
176
0
29 Apr 2014
High-dimensional estimation with geometric constraints
High-dimensional estimation with geometric constraints
Y. Plan
Roman Vershynin
E. Yudovina
127
144
0
14 Apr 2014
Sparse recovery under weak moment assumptions
Sparse recovery under weak moment assumptions
Guillaume Lecué
S. Mendelson
134
98
0
09 Jan 2014
Learning without Concentration
Learning without Concentration
S. Mendelson
166
333
0
01 Jan 2014
The Convex Geometry of Linear Inverse Problems
The Convex Geometry of Linear Inverse Problems
V. Chandrasekaran
Benjamin Recht
P. Parrilo
A. Willsky
152
1,338
0
03 Dec 2010
The solution path of the generalized lasso
The solution path of the generalized lasso
Robert Tibshirani
Jonathan E. Taylor
168
862
0
11 May 2010
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