Graph-based regularization for regression problems with alignment and
highly-correlated designs

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Graph-based regularization for regression problems with alignment and highly-correlated designs

20 March 2018

Garvesh Raskutti

Rebecca Willett

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Papers citing "Graph-based regularization for regression problems with alignment and highly-correlated designs"

13 / 13 papers shown

Title
Lasso and Partially-Rotated Designs Rares-Darius Buhai 51 0 0 16 May 2025
Feature Adaptation for Sparse Linear Regression Jonathan A. Kelner Frederic Koehler Raghu Meka Dhruv Rohatgi 52 8 0 26 May 2023
DiSC: Differential Spectral Clustering of Features Ram Dyuthi Sristi Zhengchao Wan Ariel Jaffe 41 6 0 10 Nov 2022
The Generalized Elastic Net for least squares regression with network-aligned signal and correlated design Huy Tran Sansen Wei Claire Donnat 80 3 0 01 Nov 2022
Cluster Stability Selection Gregory Faletto Jacob Bien 53 5 0 03 Jan 2022
An Optimal Reduction of TV-Denoising to Adaptive Online Learning Dheeraj Baby Xuandong Zhao Yu Wang 92 12 0 23 Jan 2021
The SPDE Approach to Matérn Fields: Graph Representations D. Sanz-Alonso Ruiyi Yang 65 19 0 16 Apr 2020
Langevin Monte Carlo without smoothness Niladri S. Chatterji Jelena Diakonikolas Michael I. Jordan Peter L. Bartlett BDL 105 43 0 30 May 2019
Iterative Alpha Expansion for estimating gradient-sparse signals from linear measurements Sheng Xu Z. Fan 38 6 0 15 May 2019
New Computational and Statistical Aspects of Regularized Regression with Application to Rare Feature Selection and Aggregation Amin Jalali Adel Javanmard Maryam Fazel 57 1 0 10 Apr 2019
Error Analysis on Graph Laplacian Regularized Estimator Kaige Yang Xiaowen Dong Laura Toni 27 1 0 11 Feb 2019
The Mismatch Principle: The Generalized Lasso Under Large Model Uncertainties Martin Genzel Gitta Kutyniok 42 2 0 20 Aug 2018
Rare Feature Selection in High Dimensions Xiaohan Yan Jacob Bien 57 38 0 18 Mar 2018