Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation

24 June 2015

Papers citing "Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation"

9 / 9 papers shown

Title
Global Convergence of Adaptive Sensing for Principal Eigenvector Estimation Alex Saad-Falcon Brighton Ancelin Justin Romberg 19 0 0 16 May 2025
Mining of Switching Sparse Networks for Missing Value Imputation in Multivariate Time Series Kohei Obata Koki Kawabata Yasuko Matsubara Yasushi Sakurai AI4TS 33 1 0 16 Sep 2024
Sharp Global Guarantees for Nonconvex Low-rank Recovery in the Noisy Overparameterized Regime Richard Y. Zhang 47 25 0 21 Apr 2021
Streaming PCA and Subspace Tracking: The Missing Data Case Laura Balzano Yuejie Chi Yue M. Lu 13 84 0 12 Jun 2018
A Well-Tempered Landscape for Non-convex Robust Subspace Recovery Tyler Maunu Teng Zhang Gilad Lerman 24 63 0 13 Jun 2017
Global Optimality of Local Search for Low Rank Matrix Recovery Srinadh Bhojanapalli Behnam Neyshabur Nathan Srebro ODL 36 386 0 23 May 2016
Dropping Convexity for Faster Semi-definite Optimization Srinadh Bhojanapalli Anastasios Kyrillidis Sujay Sanghavi 27 172 0 14 Sep 2015
Adaptive Stochastic Gradient Descent on the Grassmannian for Robust Low-Rank Subspace Recovery and Clustering Jun He Yue Zhang 30 8 0 12 Dec 2014
Fast, Robust and Non-convex Subspace Recovery Gilad Lerman Tyler Maunu 36 77 0 24 Jun 2014