Estimation of (near) low-rank matrices with noise and high-dimensional scaling

27 December 2009

Papers citing "Estimation of (near) low-rank matrices with noise and high-dimensional scaling"

29 / 29 papers shown

Title
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization G. Zhang S. Fattahi Richard Y. Zhang 38 34 0 13 Apr 2025
Exploiting Observation Bias to Improve Matrix Completion Yassir Jedra Sean Mann Charlotte Park Devavrat Shah 33 1 0 03 Jan 2025
$On properties of fractional posterior in generalized reduced-rank regression$ On properties of fractional posterior in generalized reduced-rank regression The Tien Mai 24 1 0 27 Apr 2024
Two-sided Matrix Regression Nayel Bettache C. Butucea 23 0 0 08 Mar 2023
Lag selection and estimation of stable parameters for multiple autoregressive processes through convex programming Somnath Chakraborty Johannes Lederer R. Sachs 19 0 0 03 Mar 2023
Quantized Low-Rank Multivariate Regression with Random Dithering Junren Chen Yueqi Wang Michael Kwok-Po Ng 12 4 0 22 Feb 2023
Causal Inference (C-inf) -- closed form worst case typical phase transitions A. Capponi M. Stojnic 11 2 0 02 Jan 2023
Robust and Sparse Estimation of Linear Regression Coefficients with Heavy-tailed Noises and Covariates Takeyuki Sasai 8 4 0 15 Jun 2022
Supervised Dictionary Learning with Auxiliary Covariates Joo-Hyun Lee Hanbaek Lyu W. Yao 14 1 0 14 Jun 2022
Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation Robert A. Vandermeulen Antoine Ledent 20 7 0 02 Apr 2022
Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings Kan Xu Xuanyi Zhao Hamsa Bastani Osbert Bastani 17 6 0 18 Apr 2021
Factor Models for High-Dimensional Tensor Time Series Rong Chen Dan Yang Cun-Hui Zhang AI4TS 11 90 0 18 May 2019
Tuning parameter selection rules for nuclear norm regularized multivariate linear regression Pan Shang Lingchen Kong 11 1 0 19 Jan 2019
Integrative Multi-View Reduced-Rank Regression: Bridging Group-Sparse and Low-Rank Models Gen Li Xiaokang Liu Kun Chen 8 6 0 26 Jul 2018
Foundations of Sequence-to-Sequence Modeling for Time Series Vitaly Kuznetsov Zelda E. Mariet AI4TS BDL 13 56 0 09 May 2018
Equivalent Lipschitz surrogates for zero-norm and rank optimization problems Yulan Liu Shujun Bi S. Pan 17 29 0 30 Apr 2018
Dynamic matrix recovery from incomplete observations under an exact low-rank constraint Liangbei Xu Mark A. Davenport 13 26 0 28 Oct 2016
Dynamic Assortment Personalization in High Dimensions Nathan Kallus Madeleine Udell 21 66 0 18 Oct 2016
A Unified Computational and Statistical Framework for Nonconvex Low-Rank Matrix Estimation Lingxiao Wang Xiao Zhang Quanquan Gu 9 80 0 17 Oct 2016
Robust Reduced Rank Regression Yiyuan She Kun Chen 6 58 0 14 Sep 2015
Optimal Estimation of Low Rank Density Matrices V. Koltchinskii Dong Xia 21 41 0 17 Jul 2015
CUR Algorithm for Partially Observed Matrices Miao Xu R. L. Jin Zhi-Hua Zhou 27 34 0 04 Nov 2014
Individualized Rank Aggregation using Nuclear Norm Regularization Yu Lu S. Negahban 19 44 0 03 Oct 2014
Randomized Sketches of Convex Programs with Sharp Guarantees Mert Pilanci Martin J. Wainwright 33 175 0 29 Apr 2014
Noisy low-rank matrix completion with general sampling distribution Olga Klopp 36 203 0 01 Mar 2012
A Dirty Model for Multiple Sparse Regression A. Jalali Pradeep Ravikumar Sujay Sanghavi 51 47 0 29 Jun 2011
Sharp oracle inequalities for the prediction of a high-dimensional matrix Stéphane Gaïffas Guillaume Lecué 44 27 0 28 Aug 2010
Reconstruction of a Low-rank Matrix in the Presence of Gaussian Noise A. Shabalin A. Nobel 60 161 0 23 Jul 2010
Taking Advantage of Sparsity in Multi-Task Learning Karim Lounici Massimiliano Pontil Alexandre B. Tsybakov Sara van de Geer 178 292 0 09 Mar 2009