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Manopt, a Matlab toolbox for optimization on manifolds

Manopt, a Matlab toolbox for optimization on manifolds

23 August 2013
Nicolas Boumal
Bamdev Mishra
P.-A. Absil
R. Sepulchre
ArXivPDFHTML

Papers citing "Manopt, a Matlab toolbox for optimization on manifolds"

50 / 237 papers shown
Title
Riemannian Direct Trajectory Optimization of Rigid Bodies on Matrix Lie Groups
Riemannian Direct Trajectory Optimization of Rigid Bodies on Matrix Lie Groups
Sangli Teng
Tzu-Yuan Lin
William Clark
Ram Vasudevan
Maani Ghaffari
AI4CE
52
0
0
05 May 2025
SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges
SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges
Ce Ju
Reinmar J. Kobler
Antoine Collas
M. Kawanabe
Cuntai Guan
Bertrand Thirion
53
0
0
26 Apr 2025
Riemannian Optimization on Relaxed Indicator Matrix Manifold
Riemannian Optimization on Relaxed Indicator Matrix Manifold
Jinghui Yuan
Fangyuan Xie
Feiping Nie
Xuelong Li
77
0
0
26 Mar 2025
Riemannian Geometric-based Meta Learning
JuneYoung Park
YuMi Lee
Tae Joon Kim
Jang-Hwan Choi
57
0
0
14 Mar 2025
Higher Order Reduced Rank Regression
Leia Greenberg
Haim Avron
43
0
0
09 Mar 2025
Communication-Efficient Device Scheduling for Federated Learning Using Lyapunov Optimization
Jake B. Perazzone
Shiqiang Wang
Mingyue Ji
Kevin S. Chan
FedML
75
0
0
01 Mar 2025
Spectral-factorized Positive-definite Curvature Learning for NN Training
Spectral-factorized Positive-definite Curvature Learning for NN Training
Wu Lin
Felix Dangel
Runa Eschenhagen
Juhan Bae
Richard E. Turner
Roger B. Grosse
53
0
0
10 Feb 2025
Nested subspace learning with flags
Tom Szwagier
Xavier Pennec
61
0
0
09 Feb 2025
Elliptical Wishart distributions: information geometry, maximum
  likelihood estimator, performance analysis and statistical learning
Elliptical Wishart distributions: information geometry, maximum likelihood estimator, performance analysis and statistical learning
Imen Ayadi
Florent Bouchard
Frédéric Pascal
26
1
0
05 Nov 2024
An Overview of the Burer-Monteiro Method for Certifiable Robot
  Perception
An Overview of the Burer-Monteiro Method for Certifiable Robot Perception
Alan Papalia
Yulun Tian
David M. Rosen
Jonathan P. How
John J. Leonard
43
1
0
30 Sep 2024
Riemannian Federated Learning via Averaging Gradient Stream
Riemannian Federated Learning via Averaging Gradient Stream
Zhenwei Huang
Wen Huang
Pratik Jawanpuria
Bamdev Mishra
FedML
40
1
0
11 Sep 2024
Bounds on the geodesic distances on the Stiefel manifold for a family of
  Riemannian metrics
Bounds on the geodesic distances on the Stiefel manifold for a family of Riemannian metrics
Simon Mataigne
P.-A. Absil
Nina Miolane
OT
23
2
0
25 Jul 2024
Disciplined Geodesically Convex Programming
Disciplined Geodesically Convex Programming
Andrew Cheng
Vaibhav Dixit
Melanie Weber
28
1
0
07 Jul 2024
Nonconvex Federated Learning on Compact Smooth Submanifolds With
  Heterogeneous Data
Nonconvex Federated Learning on Compact Smooth Submanifolds With Heterogeneous Data
Jiaojiao Zhang
Jiang Hu
Anthony Man-Cho So
Mikael Johansson
42
2
0
12 Jun 2024
Riemannian coordinate descent algorithms on matrix manifolds
Riemannian coordinate descent algorithms on matrix manifolds
Andi Han
Pratik Jawanpuria
Bamdev Mishra
53
5
0
04 Jun 2024
Scalable Distance-based Multi-Agent Relative State Estimation via Block
  Multiconvex Optimization
Scalable Distance-based Multi-Agent Relative State Estimation via Block Multiconvex Optimization
Tianyue Wu
Gongye Zaitian
Qianhao Wang
Fei Gao
55
4
0
31 May 2024
Synchronization on circles and spheres with nonlinear interactions
Synchronization on circles and spheres with nonlinear interactions
Christopher Criscitiello
Quentin Rebjock
Andrew D. McRae
Nicolas Boumal
41
4
0
28 May 2024
Federated Learning on Riemannian Manifolds with Differential Privacy
Federated Learning on Riemannian Manifolds with Differential Privacy
Zhenwei Huang
Wen Huang
Pratik Jawanpuria
Bamdev Mishra
FedML
47
6
0
15 Apr 2024
FireANTs: Adaptive Riemannian Optimization for Multi-Scale Diffeomorphic Matching
FireANTs: Adaptive Riemannian Optimization for Multi-Scale Diffeomorphic Matching
Rohit Jena
Pratik Chaudhari
James C. Gee
52
1
0
01 Apr 2024
Registration of algebraic varieties using Riemannian optimization
Registration of algebraic varieties using Riemannian optimization
Florentin Goyens
C. Cartis
Stéphane Chrétien
3DPC
31
0
0
16 Jan 2024
Fast, Scalable, Warm-Start Semidefinite Programming with Spectral
  Bundling and Sketching
Fast, Scalable, Warm-Start Semidefinite Programming with Spectral Bundling and Sketching
Rico Angell
Andrew McCallum
32
1
0
19 Dec 2023
Parallel Computation of Multi-Slice Clustering of Third-Order Tensors
Parallel Computation of Multi-Slice Clustering of Third-Order Tensors
Dina Faneva Andriantsiory
Camille Coti
J. B. Geloun
M. Lebbah
8
0
0
29 Sep 2023
Zeroth-order Riemannian Averaging Stochastic Approximation Algorithms
Zeroth-order Riemannian Averaging Stochastic Approximation Algorithms
Jiaxiang Li
Krishnakumar Balasubramanian
Shiqian Ma
25
2
0
25 Sep 2023
Recent Advances in Path Integral Control for Trajectory Optimization: An
  Overview in Theoretical and Algorithmic Perspectives
Recent Advances in Path Integral Control for Trajectory Optimization: An Overview in Theoretical and Algorithmic Perspectives
Muhammad Kazim
JunGee Hong
Min-Gyeom Kim
Kwang-Ki K. Kim
44
16
0
22 Sep 2023
Capacity Bounds for Hyperbolic Neural Network Representations of Latent
  Tree Structures
Capacity Bounds for Hyperbolic Neural Network Representations of Latent Tree Structures
Anastasis Kratsios
Rui Hong
Haitz Sáez de Ocáriz Borde
36
4
0
18 Aug 2023
Sparse Array Design for Direction Finding using Deep Learning
Sparse Array Design for Direction Finding using Deep Learning
Kumar Vijay Mishra
Ahmet M. Elbir
K. Ichige
17
3
0
08 Aug 2023
Multifidelity Covariance Estimation via Regression on the Manifold of
  Symmetric Positive Definite Matrices
Multifidelity Covariance Estimation via Regression on the Manifold of Symmetric Positive Definite Matrices
A. Maurais
Terrence Alsup
Benjamin Peherstorfer
Youssef Marzouk
40
3
0
23 Jul 2023
ReSync: Riemannian Subgradient-based Robust Rotation Synchronization
ReSync: Riemannian Subgradient-based Robust Rotation Synchronization
Huikang Liu
Xiao Li
Anthony Man-Cho So
32
3
0
24 May 2023
Alignment of Density Maps in Wasserstein Distance
Alignment of Density Maps in Wasserstein Distance
A. Singer
Ruiyi Yang
33
8
0
21 May 2023
Nonnegative Low-Rank Tensor Completion via Dual Formulation with
  Applications to Image and Video Completion
Nonnegative Low-Rank Tensor Completion via Dual Formulation with Applications to Image and Video Completion
Tanmay Sinha
Jayadev Naram
Pawan Kumar
39
10
0
13 May 2023
A Majorization-Minimization Gauss-Newton Method for 1-Bit Matrix
  Completion
A Majorization-Minimization Gauss-Newton Method for 1-Bit Matrix Completion
Xiaoqian Liu
Xu Han
Eric C. Chi
B. Nadler
21
0
0
27 Apr 2023
Equilibrium-Invariant Embedding, Metric Space, and Fundamental Set of
  $2\times2$ Normal-Form Games
Equilibrium-Invariant Embedding, Metric Space, and Fundamental Set of 2×22\times22×2 Normal-Form Games
Luke Marris
I. Gemp
Georgios Piliouras
16
4
0
19 Apr 2023
Differential geometry with extreme eigenvalues in the positive
  semidefinite cone
Differential geometry with extreme eigenvalues in the positive semidefinite cone
Cyrus Mostajeran
Nathael Da Costa
Graham W. Van Goffrier
R. Sepulchre
29
4
0
14 Apr 2023
Chordal Averaging on Flag Manifolds and Its Applications
Chordal Averaging on Flag Manifolds and Its Applications
Nathan Mankovich
Tolga Birdal
35
5
0
23 Mar 2023
Decentralized Riemannian natural gradient methods with Kronecker-product
  approximations
Decentralized Riemannian natural gradient methods with Kronecker-product approximations
Jiang Hu
Kangkang Deng
Na Li
Quanzheng Li
41
7
0
16 Mar 2023
Gaussian Process on the Product of Directional Manifolds
Gaussian Process on the Product of Directional Manifolds
Ziyu Cao
Kailai Li
GP
146
1
0
13 Mar 2023
Faster Riemannian Newton-type Optimization by Subsampling and Cubic
  Regularization
Faster Riemannian Newton-type Optimization by Subsampling and Cubic Regularization
Yian Deng
Tingting Mu
28
1
0
22 Feb 2023
A Survey of Geometric Optimization for Deep Learning: From Euclidean
  Space to Riemannian Manifold
A Survey of Geometric Optimization for Deep Learning: From Euclidean Space to Riemannian Manifold
Yanhong Fei
Xian Wei
Yingjie Liu
Zhengyu Li
Mingsong Chen
33
6
0
16 Feb 2023
Bayesian Learning for Neural Networks: an algorithmic survey
Bayesian Learning for Neural Networks: an algorithmic survey
M. Magris
Alexandros Iosifidis
BDL
DRL
47
68
0
21 Nov 2022
Manifold Gaussian Variational Bayes on the Precision Matrix
Manifold Gaussian Variational Bayes on the Precision Matrix
M. Magris
M. Shabani
Alexandros Iosifidis
42
2
0
26 Oct 2022
Bearing-based Relative Localization for Robotic Swarm with Partially
  Mutual Observations
Bearing-based Relative Localization for Robotic Swarm with Partially Mutual Observations
Yingjian Wang
Xiangyong Wen
Yanjun Cao
Chao Xu
Fei Gao
42
10
0
15 Oct 2022
Rieoptax: Riemannian Optimization in JAX
Rieoptax: Riemannian Optimization in JAX
Saiteja Utpala
Andi Han
Pratik Jawanpuria
Bamdev Mishra
23
3
0
10 Oct 2022
Star-Graph Multimodal Matching Component Analysis for Data Fusion and
  Transfer Learning
Star-Graph Multimodal Matching Component Analysis for Data Fusion and Transfer Learning
Nick Lorenzo
17
0
0
05 Oct 2022
Multi-View Independent Component Analysis with Shared and Individual
  Sources
Multi-View Independent Component Analysis with Shared and Individual Sources
T. Pandeva
Patrick Forré
CML
20
5
0
05 Oct 2022
NCVX: A General-Purpose Optimization Solver for Constrained Machine and
  Deep Learning
NCVX: A General-Purpose Optimization Solver for Constrained Machine and Deep Learning
Buyun Liang
Tim Mitchell
Ju Sun
OOD
23
7
0
03 Oct 2022
Cubic-Regularized Newton for Spectral Constrained Matrix Optimization
  and its Application to Fairness
Cubic-Regularized Newton for Spectral Constrained Matrix Optimization and its Application to Fairness
Casey Garner
Gilad Lerman
Shuzhong Zhang
27
0
0
02 Sep 2022
Riemannian accelerated gradient methods via extrapolation
Riemannian accelerated gradient methods via extrapolation
Andi Han
Bamdev Mishra
Pratik Jawanpuria
Junbin Gao
24
9
0
13 Aug 2022
Joint Precoding and Phase Shift Design in Reconfigurable Intelligent
  Surfaces-Assisted Secret Key Generation
Joint Precoding and Phase Shift Design in Reconfigurable Intelligent Surfaces-Assisted Secret Key Generation
Tianyu Lu
Liquan Chen
Junqing Zhang
Chen Chen
A. Hu
22
16
0
30 Jul 2022
A Kendall Shape Space Approach to 3D Shape Estimation from 2D Landmarks
A Kendall Shape Space Approach to 3D Shape Estimation from 2D Landmarks
M.W.J. Paskin
D. Baum
M. Dean
C. V. Tycowicz
17
3
0
26 Jul 2022
Riemannian Stochastic Gradient Method for Nested Composition
  Optimization
Riemannian Stochastic Gradient Method for Nested Composition Optimization
Dewei Zhang
S. Tajbakhsh
28
1
0
19 Jul 2022
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