$Minimax rates of estimation for high-dimensional linear regression over $\ell_q$-balls$

Minimax rates of estimation for high-dimensional linear regression over $\ell_q$ -balls

11 October 2009

Papers citing "Minimax rates of estimation for high-dimensional linear regression over $\ell_q$-balls"

50 / 58 papers shown

Title
Mallows-type model averaging: Non-asymptotic analysis and all-subset combination Jingfu Peng MoMe 37 0 0 05 May 2025
Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning Frederik Hoppe C. M. Verdun Hannah Laus Felix Krahmer Holger Rauhut UQCV 22 1 0 18 Jul 2024
Structured Low-Rank Tensors for Generalized Linear Models Batoul Taki Anand D. Sarwate W. Bajwa 21 2 0 05 Aug 2023
Slow Kill for Big Data Learning Yiyuan She Jianhui Shen Adrian Barbu 20 3 0 02 May 2023
Fundamental Tradeoffs in Learning with Prior Information Anirudha Majumdar 27 0 0 26 Apr 2023
PRIMO: Private Regression in Multiple Outcomes Seth Neel 23 0 0 07 Mar 2023
A distribution-free mixed-integer optimization approach to hierarchical modelling of clustered and longitudinal data Madhav Sankaranarayanan Intekhab Hossain Tom Chen 13 0 0 06 Feb 2023
The Contextual Lasso: Sparse Linear Models via Deep Neural Networks Ryan Thompson Amir Dezfouli Robert Kohn 31 4 0 02 Feb 2023
Implicit Regularization Leads to Benign Overfitting for Sparse Linear Regression Mo Zhou Rong Ge 27 2 0 01 Feb 2023
Uncertainty quantification for sparse Fourier recovery F. Hoppe Felix Krahmer C. M. Verdun Marion I. Menzel Holger Rauhut 27 7 0 30 Dec 2022
Quantizing Heavy-tailed Data in Statistical Estimation: (Near) Minimax Rates, Covariate Quantization, and Uniform Recovery Junren Chen Michael Kwok-Po Ng Di Wang MQ 24 12 0 30 Dec 2022
Spectral Regularization Allows Data-frugal Learning over Combinatorial Spaces Amirali Aghazadeh Nived Rajaraman Tony Tu Kannan Ramchandran 17 2 0 05 Oct 2022
Blessing of Nonconvexity in Deep Linear Models: Depth Flattens the Optimization Landscape Around the True Solution Jianhao Ma S. Fattahi 42 5 0 15 Jul 2022
Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers Tommaso dÓrsi Chih-Hung Liu Rajai Nasser Gleb Novikov David Steurer Stefan Tiegel 26 11 0 04 Nov 2021
A Bernstein-type Inequality for High Dimensional Linear Processes with Applications to Robust Estimation of Time Series Regressions Linbo Liu Danna Zhang AI4TS 40 1 0 21 Sep 2021
A unified precision matrix estimation framework via sparse column-wise inverse operator under weak sparsity Zeyu Wu Cheng-Long Wang Weidong Liu 28 3 0 07 Jul 2021
Mostly Harmless Machine Learning: Learning Optimal Instruments in Linear IV Models Jiafeng Chen Daniel L. Chen Greg Lewis CML 25 15 0 12 Nov 2020
Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers Fan Yang Hongyang R. Zhang Sen Wu Christopher Ré Weijie J. Su 56 10 0 22 Oct 2020
$Transfer Learning via $\ell_1$ Regularization$ Transfer Learning via $\ell_1$ Regularization Masaaki Takada Hironori Fujisawa 9 7 0 26 Jun 2020
Transfer Learning for High-dimensional Linear Regression: Prediction, Estimation, and Minimax Optimality Sai Li T. Tony Cai Hongzhe Li 38 157 0 18 Jun 2020
Sparse Regression at Scale: Branch-and-Bound rooted in First-Order Optimization Hussein Hazimeh Rahul Mazumder A. Saab 86 87 0 13 Apr 2020
An error bound for Lasso and Group Lasso in high dimensions Antoine Dedieu 11 3 0 21 Dec 2019
Does SLOPE outperform bridge regression? Shuaiwen Wang Haolei Weng A. Maleki 13 19 0 20 Sep 2019
$A unifying approach for doubly-robust $\ell_1$ regularized estimation of causal contrasts$ A unifying approach for doubly-robust $\ell_1$ regularized estimation of causal contrasts Ezequiel Smucler A. Rotnitzky J. M. Robins CML 13 76 0 07 Apr 2019
High-Dimensional Bernoulli Autoregressive Process with Long-Range Dependence Parthe Pandit Mojtaba Sahraee-Ardakan Arash A. Amini S. Rangan A. Fletcher 21 0 0 19 Mar 2019
Error bounds for sparse classifiers in high-dimensions Antoine Dedieu 20 7 0 07 Oct 2018
Approximation and Estimation for High-Dimensional Deep Learning Networks Andrew R. Barron Jason M. Klusowski 19 59 0 10 Sep 2018
Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms Hussein Hazimeh Rahul Mazumder 19 180 0 05 Mar 2018
Nearly optimal Bayesian Shrinkage for High Dimensional Regression Qifan Song F. Liang 16 76 0 24 Dec 2017
Convergence rates of least squares regression estimators with heavy-tailed errors Q. Han J. Wellner 15 44 0 07 Jun 2017
Approximate $l_0$ -penalized estimation of piecewise-constant signals on graphs Z. Fan Leying Guan 26 21 0 04 Mar 2017
Adaptive Risk Bounds in Univariate Total Variation Denoising and Trend Filtering Adityanand Guntuboyina Donovan Lieu S. Chatterjee B. Sen 23 66 0 16 Feb 2017
Robust Regression via Mutivariate Regression Depth Chao Gao 24 48 0 15 Feb 2017
Minimax Lower Bounds for Ridge Combinations Including Neural Nets Jason M. Klusowski Andrew R. Barron 27 22 0 09 Feb 2017
Optimal Kullback-Leibler Aggregation in Mixture Density Estimation by Maximum Likelihood A. Dalalyan M. Sebbar FedML 36 9 0 18 Jan 2017
Dynamic Pricing in High-dimensions Adel Javanmard Hamid Nazerzadeh 66 136 0 24 Sep 2016
The DFS Fused Lasso: Linear-Time Denoising over General Graphs Oscar Hernan Madrid Padilla James G. Scott James Sharpnack R. Tibshirani FedML 34 67 0 11 Aug 2016
Ridge regression and asymptotic minimax estimation over spheres of growing dimension Lee H. Dicker 22 75 0 15 Jan 2016
Learning Directed Acyclic Graphs with Penalized Neighbourhood Regression Bryon Aragam Arash A. Amini Qing Zhou CML 19 42 0 29 Nov 2015
Consistent Parameter Estimation for LASSO and Approximate Message Passing Ali Mousavi A. Maleki Richard G. Baraniuk 11 58 0 03 Nov 2015
A Geometric View on Constrained M-Estimators Yen-Huan Li Ya-Ping Hsieh N. Zerbib V. Cevher 19 6 0 26 Jun 2015
A General Framework for Bayes Structured Linear Models Chao Gao A. van der Vaart Harrison H. Zhou 34 57 0 06 Jun 2015
Implementable confidence sets in high dimensional regression Alexandra Carpentier 27 4 0 19 Jan 2015
Pathwise Coordinate Optimization for Sparse Learning: Algorithm and Theory T. Zhao Han Liu Tong Zhang 32 46 0 23 Dec 2014
Sparse Modeling for Image and Vision Processing Julien Mairal Francis R. Bach Jean Ponce VLM 37 487 0 12 Nov 2014
High Dimensional Semiparametric Scale-Invariant Principal Component Analysis Fang Han Han Liu 40 16 0 18 Feb 2014
An RKHS Approach to Estimation with Sparsity Constraints A. Jung 40 3 0 22 Nov 2013
Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima Po-Ling Loh Martin J. Wainwright 26 512 0 10 May 2013
The Lasso for High-Dimensional Regression with a Possible Change-Point S. Lee M. Seo Youngki Shin 66 124 0 21 Sep 2012
Nearly optimal minimax estimator for high-dimensional sparse linear regression Li Zhang 38 12 0 27 Jun 2012