A Brief Introduction to Manifold Optimization

Type: Article

Publication Date: 2020-04-04

Citations: 145

DOI: https://doi.org/10.1007/s40305-020-00295-9

View Chat PDF

Abstract

Abstract Manifold optimization is ubiquitous in computational and applied mathematics, statistics, engineering, machine learning, physics, chemistry, etc. One of the main challenges usually is the non-convexity of the manifold constraints. By utilizing the geometry of manifold, a large class of constrained optimization problems can be viewed as unconstrained optimization problems on manifold. From this perspective, intrinsic structures, optimality conditions and numerical algorithms for manifold optimization are investigated. Some recent progress on the theoretical results of manifold optimization is also presented.

Locations

  • Journal of the Operations Research Society of China - View - PDF

Similar Works

Action Title Year Authors
+ A Brief Introduction to Manifold Optimization 2019 Jiang Hu
Xin Liu
Zaiwen Wen
Ya-xiang Yuan
+ An Introduction to Optimization on Smooth Manifolds 2023 Nicolas Boumal
+ MADMM: a generic algorithm for non-smooth optimization on manifolds 2015 Artiom Kovnatsky
Klaus Glashoff
Michael M. Bronstein
+ MADMM: a generic algorithm for non-smooth optimization on manifolds 2015 Artiom Kovnatsky
Klaus Glashoff
Michael M. Bronstein
+ Simple algorithms for optimization on Riemannian manifolds with constraints 2019 Changshuo Liu
Nicolas Boumal
+ PDF Chat Simple Algorithms for Optimization on Riemannian Manifolds with Constraints 2019 Changshuo Liu
Nicolas Boumal
+ Optimization On Manifolds: Methods and Applications 2010 Pierre-Antoine Absil
Robert Mahony
Rodolphe Sepulchre
+ Uniform Framework for Unconstrained and Constrained Optimization: Optimization on Riemannian Manifolds 2010 Yiguang Yang
+ Preliminaries and Overview of Euclidean Optimization 2021 Hiroyuki Sato
+ A manifold inexact augmented Lagrangian method for nonsmooth optimization on Riemannian submanifolds in Euclidean space 2022 Kangkang Deng
Peng Zheng
+ Manifold Free Riemannian Optimization 2022 Boris Shustin
Haim Avron
Barak Sober
+ Manifold Fitting 2023 Zhigang Yao
Jiaji Su
Bingjie Li
+ Optimization on Riemannian manifold 2003 Yaguang Yang
+ CDOpt: A Python Package for a Class of Riemannian Optimization 2022 Nachuan Xiao
Xiaoyin Hu
Xin Liu
Kim-Chuan Toh
+ The Manopt toolbox: making optimization on manifolds easy 2013 Nicolas Boumal
Bamdev Mishra
+ Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds 2020 Lizhen Lin
Bayan Saparbayeva
Michael Minyi Zhang
David B. Dunson
+ PDF Chat Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds 2020 Lizhen Lin
Bayan Saparbayeva
Michael Minyi Zhang
David B. Dunson
+ An inexact augmented Lagrangian method for nonsmooth optimization on Riemannian manifold 2019 Kangkang Deng
Zheng Peng
+ A manifold imbedding algorithm for optimization problems 1972 Y. Hontoir
J.B. Cruz
+ A Manifold Imbedding Algorithm for Optimization Problems 1972 Y. Hontoir
Jorge Cruz

Cited by (106)

Action Title Year Authors
+ Two hybrid conjugate gradient based algorithms on Riemannian manifolds with adaptive restart strategy for nonconvex optimization problems 2024 Minghu Jiang
Yun Wang
Hu Shao
Ting Wu
Weiwei Sun
+ PDF Chat Riemannian Langevin algorithm for solving semidefinite programs 2023 Mufan Li
Murat A. Erdogdu
+ A collection of efficient retractions for the symplectic Stiefel manifold 2023 Harry Oviedo
Rafael Herrera
+ Conjugate Gradient Methods for Optimization Problems on Symplectic Stiefel Manifold 2023 M. Hirosawa Y. Yamada
Hiroyuki Sato
+ A hybrid Riemannian conjugate gradient method for nonconvex optimization problems 2022 Chunming Tang
Xianglin Rong
Jinbao Jian
Shajie Xing
+ PDF Chat Riemannian Stochastic Variance-Reduced Cubic Regularized Newton Method for Submanifold Optimization 2022 Dewei Zhang
Sam Davanloo Tajbakhsh
+ Trace Lasso Regularization for Adaptive Sparse Canonical Correlation Analysis via Manifold Optimization Approach 2022 Kangkang Deng
Zheng Peng
+ Proximal Gradient/Semismooth Newton Methods for Projection onto a Polyhedron via the Duality-Gap-Active-Set Strategy 2023 Yunlong Wang
Chungen Shen
Lei‐Hong Zhang
Wei Hong Yang
+ Solving Optimization Problems over the Stiefel Manifold by Smooth Exact Penalty Function 2021 Nachuan Xiao
Xin Liu
+ PDF Chat Dissolving Constraints for Riemannian Optimization 2023 Nachuan Xiao
Xin Liu
Kim-Chuan Toh
+ An active-set proximal quasi-Newton algorithm for ℓ<sub>1</sub>-regularized minimization over a sphere constraint 2021 Chungen Shen
Ling Mi
Lei‐Hong Zhang
+ Multipliers Correction Methods for Optimization Problems over the Stiefel Manifold 2020 Lei Wang
Bin Gao
Xin Liu
+ PDF Chat A constraint dissolving approach for nonsmooth optimization over the Stiefel manifold 2023 Xiaoyin Hu
Nachuan Xiao
Xin Liu
Kim-Chuan Toh
+ A Penalty-Free Infeasible Approach for a Class of Nonsmooth Optimization Problems Over the Stiefel Manifold 2024 Xin Liu
Nachuan Xiao
Ya-xiang Yuan
+ Optimization schemes on manifolds for structured matrices with fixed eigenvalues 2024 Jean‐Paul Chehab
Harry Oviedo
Marcos Raydan
+ PDF Chat New vector transport operators extending a Riemannian CG algorithm to generalized Stiefel manifold with low-rank applications 2024 Xuejie Wang
Kangkang Deng
Zheng Peng
Chengcheng Yan
+ Computation over t-Product Based Tensor Stiefel Manifold: A Preliminary Study 2024 Xianpeng Mao
Ying Wang
Yuning Yang
+ On Constraint Qualifications for Mathematical Programming Problems with Vanishing Constraints on Hadamard Manifolds 2023 Balendu Bhooshan Upadhyay
Arnav Ghosh
+ PDF Chat Solving graph equipartition SDPs on an algebraic variety 2023 Tianyun Tang
Kim-Chuan Toh
+ Two efficient nonlinear conjugate gradient methods for Riemannian manifolds 2024 Nasiru Salihu
Poom Kumam
Sani Salisu
+ An accelerated hybrid Riemannian conjugate gradient method for unconstrained optimization 2024 Jinchao Zhang
Wei Zhu
Wei Wang
Zhaochong Wu
Xiaojun Zhang
+ PDF Chat Quantifying subspace entanglement with geometric measures 2024 Xuanran Zhu
Chao Zhang
Bei Zeng
+ Riemannian conjugate gradient methods with inverse retraction 2020 Xiaojing Zhu
Hiroyuki Sato
+ KKT Conditions, First-Order and Second-Order Optimization, and Distributed Optimization: Tutorial and Survey 2021 Benyamin Ghojogh
Ali Ghodsi
Fakhri Karray
Mark Crowley
+ Proximal gradient algorithm with trust region scheme on Riemannian manifold 2023 Shimin Zhao
Yan Tao
Yuanguo Zhu
+ Adaptive Trust-Region Method on Riemannian Manifold 2023 Shimin Zhao
Tao Yan
Kai Wang
Yuanguo Zhu
+ A Survey of Geometric Optimization for Deep Learning: From Euclidean Space to Riemannian Manifold 2024 Yanhong Fei
Yingjie Liu
Chentao Jia
LI Zheng-yu
Xian Wei
Mingsong Chen
+ Multipliers Correction Methods for Optimization Problems over the Stiefel Manifold 2021 Lei Wang
Bin Gao
Xin Liu
+ An inertial Mann algorithm for nonexpansive mappings on Hadamard manifolds 2022 Konrawut Khammahawong
Parin Chaipunya
Poom Kumam
+ Duality for Multiobjective Programming Problems with Equilibrium Constraints on Hadamard Manifolds under Generalized Geodesic Convexity 2023 Balendu Bhooshan Upadhyay
Arnav Ghosh
I‎. ‎M‎. Stancu-Minasian
+ A class of spectral conjugate gradient methods for Riemannian optimization 2023 Chunming Tang
Wancheng Tan
Shajie Xing
Haiyan Zheng
+ Two novel vector transports for generalized Stiefel manifold with non-standard metrics and its application to Riemannian conjugate gradient method 2023 Xuejie Wang
Kangkang Deng
Peng Zheng
Chengcheng Yan
+ PDF Chat Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods 2021 Xiao Li
Shixiang Chen
Zengde Deng
Qing Qu
Zhihui Zhu
Anthony Man-Cho So
+ PDF Chat Proximal Point Algorithm with Euclidean Distance on the Stiefel Manifold 2023 Harry Oviedo
+ PDF Chat Sequential Quadratic Optimization for Nonlinear Optimization Problems on Riemannian Manifolds 2022 Mitsuaki Obara
Takayuki Okuno
Akiko Takeda
+ PDF Chat A semismooth Newton based augmented Lagrangian method for nonsmooth optimization on matrix manifolds 2022 Yuhao Zhou
Chenglong Bao
Chao Ding
Jun Zhu
+ PDF Chat A Riemannian rank-adaptive method for low-rank matrix completion 2021 Bin Gao
Pierre-Antoine Absil
+ PDF Chat A Derivative-Free Geometric Algorithm for Optimization on a Sphere 2020 Yannan Chen
Min Xi
Hongchao Zhang
+ A Riemannian rank-adaptive method for low-rank matrix completion 2021 Bin Gao
Pierre-Antoine Absil
+ PDF Chat On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-Rank Matrix Optimization 2023 Yuetian Luo
Xudong Li
Anru R. Zhang

Citing (93)

Action Title Year Authors
+ PDF Chat An Efficient Gauss--Newton Algorithm for Symmetric Low-Rank Product Matrix Approximations 2015 Xin Liu
Zaiwen Wen
Yin Zhang
+ Numerical Optimization Methods on Riemannian Manifolds 2011 Chunhong Qi
+ PDF Chat A Second Order Nonsmooth Variational Model for Restoring Manifold-Valued Images 2016 Miroslav Bačák
Ronny Bergmann
Gabriele Steidl
Andreas Weinmann
+ Lectures on Harmonic Maps 1997 Richard Schoen
Shing Tung Yau
+ PDF Chat Trace-Penalty Minimization for Large-Scale Eigenspace Computation 2015 Zaiwen Wen
Chao Yang
Xin Liu
Yin Zhang
+ Convergence of inexact descent methods for nonconvex optimization on Riemannian manifolds 2011 G. C. Bento
João Xavier da Cruz Neto
P. R. Oliveira
+ PDF Chat Non-Negative Principal Component Analysis: Message Passing Algorithms and Sharp Asymptotics 2015 Andrea Montanari
Émile Richard
+ PDF Chat A Broyden Class of Quasi-Newton Methods for Riemannian Optimization 2015 Wen Huang
Kyle A. Gallivan
Pierre-Antoine Absil
+ Optimization Algorithms on Matrix Manifolds 2007 P.-A. Absil
Robert Mahony
Rodolphe Sepulchre
+ PDF Chat Optimization techniques on Riemannian manifolds 1995 Steven J. Smith
+ PDF Chat Limited Memory Block Krylov Subspace Optimization for Computing Dominant Singular Value Decompositions 2013 Xin Liu
Zaiwen Wen
Yin Zhang
+ A Riemannian symmetric rank-one trust-region method 2014 Wen Huang
Pierre-Antoine Absil
Kyle A. Gallivan
+ PDF Chat Minimizing a differentiable function over a differential manifold 1982 Daniel Gabay
+ PDF Chat A majorization algorithm for constrained correlation matrix approximation 2009 Dan Simon
Jeff Abell
+ On the Rank of Extreme Matrices in Semidefinite Programs and the Multiplicity of Optimal Eigenvalues 1998 Gábor Pataki
+ Convergence acceleration of iterative sequences. the case of scf iteration 1980 Péter Pulay
+ PDF Chat The Geometry of Algorithms with Orthogonality Constraints 1998 Alan Edelman
T. A. Arias
Steven T. Smith
+ Low-Rank Matrix Completion by Riemannian Optimization 2013 Bart Vandereycken
+ PDF Chat Low-rank tensor completion by Riemannian optimization 2013 Daniel Kreßner
Michael Steinlechner
Bart Vandereycken
+ PDF Chat A feasible method for optimization with orthogonality constraints 2012 Zaiwen Wen
Wotao Yin
+ Convex Functions and Optimization Methods on Riemannian Manifolds 1994 Constantin Udrişte
+ PDF Chat Projection-like Retractions on Matrix Manifolds 2012 P.-A. Absil
Jérôme Malick
+ PDF Chat Approximating the little Grothendieck problem over the orthogonal and unitary groups 2016 Afonso S. Bandeira
Christopher Kennedy
Amit Singer
+ PDF Chat A framework of constraint preserving update schemes for optimization on Stiefel manifold 2014 Bo Jiang
Yu‐Hong Dai
+ Trust-Region Methods on Riemannian Manifolds 2006 Pierre-Antoine Absil
Christopher G. Baker
Kyle A. Gallivan
+ PDF Chat A Modified Principal Component Technique Based on the LASSO 2003 Ian T. Jolliffe
Nickolay T. Trendafilov
Mudassir Uddin
+ PDF Chat Low-Rank Optimization on the Cone of Positive Semidefinite Matrices 2010 Michel Journée
Francis Bach
Pierre-Antoine Absil
Rodolphe Sepulchre
+ Local Minima and Convergence in Low-Rank Semidefinite Programming 2004 Samuel Burer
Renato D. C. Monteiro
+ A nonlinear programming algorithm for solving semidefinite programs via low-rank factorization 2003 Samuel Burer
Renato D. C. Monteiro
+ A Nonmonotone Line Search Technique and Its Application to Unconstrained Optimization 2004 Hongchao Zhang
William W. Hager
+ PDF Chat Nonsmooth trust region algorithms for locally Lipschitz functions on Riemannian manifolds 2015 Philipp Grohs
S. Hosseini
+ A New Approach to the Proximal Point Method: Convergence on General Riemannian Manifolds 2016 Glaydston de Carvalho Bento
João Xavier da Cruz Neto
Paulo Roberto Oliveira
+ Maximization of the sum of the trace ratio on the Stiefel manifold, II: Computation 2014 LeiHong Zhang
Ren‐Cang Li
+ First-order Methods for Geodesically Convex Optimization 2016 Hongyi Zhang
Suvrit Sra
+ PDF Chat Near-optimal stochastic approximation for online principal component estimation 2017 Chris Junchi Li
Mengdi Wang
Han Liu
Tong Zhang
+ PDF Chat Global rates of convergence for nonconvex optimization on manifolds 2018 Nicolas Boumal
P-A Absil
Coralia Cartis
+ A note on semidefinite programming relaxations for polynomial optimization over a single sphere 2016 Jiang Hu
Bo Jiang
Xin Liu
Zaiwen Wen
+ Subspace Methods with Local Refinements for Eigenvalue Computation Using Low-Rank Tensor-Train Format 2016 Junyu Zhang
Zaiwen Wen
Yin Zhang
+ PDF Chat Iteration-Complexity of Gradient, Subgradient and Proximal Point Methods on Riemannian Manifolds 2017 G. C. Bento
O. P. Ferreira
Jefferson G. Melo
+ Intrinsic representation of tangent vectors and vector transports on matrix manifolds 2016 Wen Huang
Pierre-Antoine Absil
Kyle A. Gallivan