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Finite-sample analysis of M-estimators using self-concordance

16 October 2018

Papers citing "Finite-sample analysis of M-estimators using self-concordance"

30 / 30 papers shown

Title
Generalized Linear Markov Decision Process Sinian Zhang Kaicheng Zhang Ziping Xu Tianxi Cai D. Zhou 37 0 0 01 Jun 2025
On the Efficiency of ERM in Feature Learning Ayoub El Hanchi Chris J. Maddison Murat A. Erdogdu 118 0 0 18 Nov 2024
Almost Free: Self-concordance in Natural Exponential Families and an Application to Bandits Shuai Liu Alex Ayoub Flore Sentenac Xiaoqi Tan Csaba Szepesvári 81 1 0 01 Oct 2024
Multiply Robust Estimation for Local Distribution Shifts with Multiple Domains Steven Wilkins-Reeves Xu Chen Qianying Ma Christine Agarwal A. Hofleitner OOD 65 1 0 21 Feb 2024
Overcoming Saturation in Density Ratio Estimation by Iterated Regularization Lukas Gruber Markus Holzleitner Johannes Lehner Sepp Hochreiter Werner Zellinger 117 2 0 21 Feb 2024
Optimal Excess Risk Bounds for Empirical Risk Minimization on $p$ -Norm Linear Regression Ayoub El Hanchi Murat A. Erdogdu 115 2 0 19 Oct 2023
Self-concordant Smoothing for Large-Scale Convex Composite Optimization Adeyemi Damilare Adeoye Alberto Bemporad 49 1 0 04 Sep 2023
A Differentially Private Weighted Empirical Risk Minimization Procedure and its Application to Outcome Weighted Learning S. Giddens Yiwang Zhou K. Krull T. Brinkman P. Song Fan Liu 66 1 0 24 Jul 2023
On the sample complexity of parameter estimation in logistic regression with normal design Daniel J. Hsu A. Mazumdar 61 7 0 09 Jul 2023
The SSL Interplay: Augmentations, Inductive Bias, and Generalization Vivien A. Cabannes B. Kiani Randall Balestriero Yann LeCun A. Bietti SSL 92 33 0 06 Feb 2023
Confidence Sets under Generalized Self-Concordance Lang Liu Zaïd Harchaoui 51 1 0 31 Dec 2022
Statistical and Computational Guarantees for Influence Diagnostics Jillian R. Fisher Lang Liu Krishna Pillutla Y. Choi Zaïd Harchaoui TDI 61 0 0 08 Dec 2022
A Conditional Randomization Test for Sparse Logistic Regression in High-Dimension Binh Duc Nguyen Bertrand Thirion Sylvain Arlot 26 6 0 29 May 2022
Orthogonal Statistical Learning with Self-Concordant Loss Lang Liu Carlos Cinelli Zaïd Harchaoui 50 2 0 30 Apr 2022
Non-Asymptotic Guarantees for Robust Statistical Learning under Infinite Variance Assumption Lihu Xu Fang Yao Qiuran Yao Huiming Zhang 69 11 0 10 Jan 2022
SCORE: Approximating Curvature Information under Self-Concordant Regularization Adeyemi Damilare Adeoye Alberto Bemporad 44 4 0 14 Dec 2021
Convergence Rates for the MAP of an Exponential Family and Stochastic Mirror Descent -- an Open Problem Rémi Le Priol Frederik Kunstner Damien Scieur Simon Lacoste-Julien 30 1 0 12 Nov 2021
Mixability made efficient: Fast online multiclass logistic regression Rémi Jézéquel Pierre Gaillard Alessandro Rudi 76 11 0 08 Oct 2021
Learning to be Fair: A Consequentialist Approach to Equitable Decision-Making Alex Chohlas-Wood Madison Coots Henry Zhu Emma Brunskill Sharad Goel FaML 84 25 0 18 Sep 2021
Scalable Frank-Wolfe on Generalized Self-concordant Functions via Simple Steps Alejandro Carderera Mathieu Besançon Sebastian Pokutta 106 6 0 28 May 2021
Differentially private inference via noisy optimization Marco Avella-Medina Casey Bradshaw Po-Ling Loh FedML 103 31 0 19 Mar 2021
Near-Optimal Procedures for Model Discrimination with Non-Disclosure Properties Dmitrii Ostrovskii M. Ndaoud Adel Javanmard Meisam Razaviyayn FedML 39 0 0 04 Dec 2020
Non-asymptotic Optimal Prediction Error for Growing-dimensional Partially Functional Linear Models Huiming Zhang Xiaoyu Lei 62 1 0 10 Sep 2020
A Newton Frank-Wolfe Method for Constrained Self-Concordant Minimization Deyi Liu Volkan Cevher Quoc Tran-Dinh 84 15 0 17 Feb 2020
Self-Concordant Analysis of Frank-Wolfe Algorithms Pavel Dvurechensky P. Ostroukhov K. Safin Shimrit Shtern Mathias Staudigl 103 24 0 11 Feb 2020
Stochastic Online Optimization using Kalman Recursion Joseph de Vilmarest Olivier Wintenberger 52 9 0 10 Feb 2020
An improper estimator with optimal excess risk in misspecified density estimation and logistic regression Jaouad Mourtada Stéphane Gaïffas 108 29 0 23 Dec 2019
A Diffusion Process Perspective on Posterior Contraction Rates for Parameters Wenlong Mou Nhat Ho Martin J. Wainwright Peter L. Bartlett Michael I. Jordan 57 16 0 03 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 85 80 0 07 Apr 2019
Beyond Least-Squares: Fast Rates for Regularized Empirical Risk Minimization through Self-Concordance Ulysse Marteau-Ferey Dmitrii Ostrovskii Francis R. Bach Alessandro Rudi 188 52 0 08 Feb 2019