Projects
Reading
People
Chat
SU\G
(đ¸)
/K¡U
Projects
Reading
People
Chat
Sign Up
Light
Dark
System
The local convexity of solving systems of quadratic equations
Chris D. White
,
Sujay Sanghavi
,
Rachel Ward
Type:
Preprint
Publication Date:
2015-06-25
Citations:
29
View Publication
Share
Locations
arXiv (Cornell University) -
View
Similar Works
Action
Title
Year
Authors
+
The local convexity of solving systems of quadratic equations
2015
Chris D. White
Sujay Sanghavi
Rachel Ward
+
PDF
Chat
The Local Convexity of Solving Systems of Quadratic Equations
2016
Sujay Sanghavi
Rachel Ward
Chris D. White
+
The Local Convexity of Solving Quadratic Equations
2015
Chris D. White
Rachel Ward
Sujay Sanghavi
+
Provable non-convex projected gradient descent for a class of constrained matrix optimization problems.
2016
Dohyung Park
Anastasios Kyrillidis
Srinadh Bhojanapalli
Constantine Caramanis
Sujay Sanghavi
+
Solving Systems of Quadratic Equations via Exponential-type Gradient Descent Algorithm
2018
Meng Huang
Zhiqiang Xu
+
Provable Burer-Monteiro factorization for a class of norm-constrained matrix problems
2016
Dohyung Park
Anastasios Kyrillidis
Srinadh Bhojanapalli
Constantine Caramanis
Sujay Sanghavi
+
Provable Burer-Monteiro factorization for a class of norm-constrained matrix problems
2016
Dohyung Park
Anastasios Kyrillidis
Srinadh Bhojanapalli
Constantine Caramanis
Sujay Sanghavi
+
Nonconvex Matrix Factorization From Rank-One Measurements
2021
Yuanxin Li
Cong Ma
Yuxin Chen
Yuejie Chi
+
Nonconvex Matrix Factorization from Rank-One Measurements
2018
YuanâXin Li
Cong Ma
Yuxin Chen
Yuejie Chi
+
Nonconvex Matrix Factorization from Rank-One Measurements
2018
YuanâXin Li
Cong Ma
Yuxin Chen
Yuejie Chi
+
Low-Rank Positive Semidefinite Matrix Recovery from Quadratic Measurements with Outliers
2016
YuanâXin Li
Yue Sun
Yuejie Chi
+
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization
2016
Xingguo Li
Junwei Lu
Raman Arora
Jarvis Haupt
Han Liu
Zhaoran Wang
Tuo Zhao
+
A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements
2015
Qinqing Zheng
John Lafferty
+
A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements
2015
Qinqing Zheng
John Lafferty
+
Global Optimality of Local Search for Low Rank Matrix Recovery
2016
Srinadh Bhojanapalli
Behnam Neyshabur
Nathan Srebro
+
Local Linear Convergence of Gradient Methods for Subspace Optimization via Strict Complementarity
2022
Dan Garber
Ron Fisher
+
Global optimality of local search for low rank matrix recovery
2016
Srinadh Bhojanapalli
Behnam Neyshabur
Nathan Srebro
+
Structured signal recovery from quadratic measurements: Breaking sample complexity barriers via nonconvex optimization
2017
Mahdi Soltanolkotabi
+
Structured signal recovery from quadratic measurements: Breaking sample complexity barriers via nonconvex optimization
2017
Mahdi Soltanolkotabi
+
Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction
2021
Dominik StĂśger
Mahdi Soltanolkotabi
Works That Cite This (26)
Action
Title
Year
Authors
+
Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems
2015
Yuxin Chen
Emmanuel J. Candès
+
PDF
Chat
Guarantees of riemannian optimization for low rank matrix completion
2020
Ke Wei
JianâFeng Cai
Tony F. Chan
Shingyu Leung
+
Toward the Optimal Construction of a Loss Function Without Spurious Local Minima for Solving Quadratic Equations
2019
Zhenzhen Li
JianâFeng Cai
Ke Wei
+
When Are Nonconvex Problems Not Scary?
2015
Ju Sun
Qing Qu
John Wright
+
Guarantees of Riemannian Optimization for Low Rank Matrix Completion
2016
Ke Wei
JianâFeng Cai
Tony F. Chan
Shingyu Leung
+
Towards the optimal construction of a loss function without spurious local minima for solving quadratic equations
2018
Zhenzhen Li
JianâFeng Cai
Ke Wei
+
Dropping Convexity for Faster Semi-definite Optimization
2015
Srinadh Bhojanapalli
Anastasios Kyrillidis
Sujay Sanghavi
+
Low-Rank Positive Semidefinite Matrix Recovery From Corrupted Rank-One Measurements
2016
Yuanxin Li
Yue Sun
Yuejie Chi
+
An Overview of Low-Rank Matrix Recovery From Incomplete Observations
2016
Mark A. Davenport
Justin Romberg
+
Complete Dictionary Recovery Over the Sphere II: Recovery by Riemannian Trust-Region Method
2016
Ju Sun
Qing Qu
John Wright
Works Cited by This (25)
Action
Title
Year
Authors
+
None
2003
V. Bentkus
+
Reconstruction of Signals from Magnitudes of Redundant Representations
2012
Radu BÄlan
+
PDF
Chat
A useful variant of the DavisâKahan theorem for statisticians
2015
Yi Yu
Tengyao Wang
Richard J. Samworth
+
PDF
Chat
Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
2006
Emmanuel J. Candès
Terence Tao
+
PDF
Chat
Stable Optimizationless Recovery from Phaseless Linear Measurements
2013
Laurent Demanet
Paul Hand
+
PDF
Chat
Painless Reconstruction from Magnitudes of Frame Coefficients
2009
Radu BÄlan
Bernhard G. Bodmann
Peter G. Casazza
Dan Edidin
+
On signal reconstruction without phase
2005
Radu BÄlan
Pete Casazza
Dan Edidin
+
Global Convergence of Stochastic Gradient Descent for Some Non-convex Matrix Problems
2014
Christopher De
Christopher RĂŠ
Kunle Olukotun
+
PDF
Chat
User-Friendly Tail Bounds for Sums of Random Matrices
2011
Joel A. Tropp
+
Low rank matrix recovery from rank one measurements
2014
Richard Kueng
Holger Rauhut
Ulrich Terstiege