First-order Methods for Geodesically Convex Optimization

19 February 2016

Papers citing "First-order Methods for Geodesically Convex Optimization"

50 / 69 papers shown

Title
Decentralized Optimization on Compact Submanifolds by Quantized Riemannian Gradient Tracking Jun Chen Lina Liu T. Zhu Yong Liu Guang Dai Yunliang Jiang Ivor Tsang 22 0 0 09 Jun 2025
Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization Dai Hai Nguyen Hiroshi Mamitsuka Atsuyoshi Nakamura 65 0 0 24 May 2025
Geodesic Optimization for Predictive Shift Adaptation on EEG data Apolline Mellot Antoine Collas Sylvain Chevallier Alexandre Gramfort Denis A. Engemann OOD 84 5 0 04 Jul 2024
CLOSURE: Fast Quantification of Pose Uncertainty Sets Yihuai Gao Yukai Tang Han Qi Heng Yang 90 6 0 15 Mar 2024
A Framework for Bilevel Optimization on Riemannian Manifolds Andi Han Bamdev Mishra Pratik Jawanpuria Akiko Takeda 81 5 0 06 Feb 2024
Robust Signal Recovery in Hadamard Spaces Georg Kostenberger Thomas Stark 47 2 0 12 Jul 2023
Low-complexity subspace-descent over symmetric positive definite manifold Yogesh Darmwal K. Rajawat 108 3 0 03 May 2023
Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties David Martínez-Rubio Sebastian Pokutta 82 10 0 26 Nov 2022
Lifting Weak Supervision To Structured Prediction Harit Vishwakarma Nicholas Roberts Frederic Sala NoLa 93 8 0 24 Nov 2022
Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery Tyler Maunu Thibaut Le Gouic Philippe Rigollet 64 5 0 26 Oct 2022
Shape And Structure Preserving Differential Privacy Carlos Soto Karthik Bharath M. Reimherr Aleksandra B. Slavkovic 61 8 0 21 Sep 2022
The Proxy Step-size Technique for Regularized Optimization on the Sphere Manifold Fang Bai Adrien Bartoli 15 1 0 05 Sep 2022
Riemannian accelerated gradient methods via extrapolation Andi Han Bamdev Mishra Pratik Jawanpuria Junbin Gao 70 10 0 13 Aug 2022
$A Particle-Based Algorithm for Distributional Optimization on \textit{Constrained Domains} via Variational Transport and Mirror Descent$ A Particle-Based Algorithm for Distributional Optimization on \textit{Constrained Domains} via Variational Transport and Mirror Descent Dai Hai Nguyen Tetsuya Sakurai 102 2 0 01 Aug 2022
Riemannian stochastic approximation algorithms Mohammad Reza Karimi Ya-Ping Hsieh P. Mertikopoulos Andreas Krause 50 2 0 14 Jun 2022
Federated Learning on Riemannian Manifolds Jiaxiang Li Shiqian Ma FedML 79 13 0 12 Jun 2022
Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport Lingkai Kong Yuqing Wang Molei Tao ODL 67 9 0 27 May 2022
Stochastic and Private Nonconvex Outlier-Robust PCA Tyler Maunu Chenyun Yu Gilad Lerman 122 3 0 17 Mar 2022
Online Learning to Transport via the Minimal Selection Principle Wenxuan Guo Y. Hur Tengyuan Liang Christopher Ryan 53 3 0 09 Feb 2022
Nonconvex Stochastic Scaled-Gradient Descent and Generalized Eigenvector Problems C. J. Li Michael I. Jordan 73 2 0 29 Dec 2021
Understanding Riemannian Acceleration via a Proximal Extragradient Framework Jikai Jin S. Sra 31 6 0 04 Nov 2021
Distributed Principal Component Analysis with Limited Communication Foivos Alimisis Peter Davies Bart Vandereycken Dan Alistarh 80 12 0 27 Oct 2021
Mode and Ridge Estimation in Euclidean and Directional Product Spaces: A Mean Shift Approach Yikun Zhang Yen-Chi Chen 151 1 0 16 Oct 2021
Universal Approximation Under Constraints is Possible with Transformers Anastasis Kratsios Behnoosh Zamanlooy Tianlin Liu Ivan Dokmanić 139 28 0 07 Oct 2021
From the Greene--Wu Convolution to Gradient Estimation over Riemannian Manifolds Tianyu Wang Yifeng Huang Didong Li 40 8 0 17 Aug 2021
Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent Jason M. Altschuler Sinho Chewi P. Gerber Austin J. Stromme 87 37 0 16 Jun 2021
On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry Andi Han Bamdev Mishra Pratik Jawanpuria Junbin Gao 105 39 0 01 Jun 2021
Universal Regular Conditional Distributions Anastasis Kratsios 97 3 0 17 May 2021
On Riemannian Stochastic Approximation Schemes with Fixed Step-Size Alain Durmus P. Jiménez Eric Moulines Salem Said 56 12 0 15 Feb 2021
Fast and accurate optimization on the orthogonal manifold without retraction Pierre Ablin Gabriel Peyré 115 30 0 15 Feb 2021
Decentralized Riemannian Gradient Descent on the Stiefel Manifold Shixiang Chen Alfredo García Mingyi Hong Shahin Shahrampour 86 45 0 14 Feb 2021
On the Local Linear Rate of Consensus on the Stiefel Manifold Shixiang Chen Alfredo García Mingyi Hong Shahin Shahrampour 61 14 0 22 Jan 2021
No-go Theorem for Acceleration in the Hyperbolic Plane Linus Hamilton Ankur Moitra 60 21 0 14 Jan 2021
Accelerating Training of Batch Normalization: A Manifold Perspective Mingyang Yi 47 3 0 08 Jan 2021
Stochastic Approximation for Online Tensorial Independent Component Analysis C. J. Li Michael I. Jordan 72 2 0 28 Dec 2020
Global Riemannian Acceleration in Hyperbolic and Spherical Spaces David Martínez-Rubio 123 20 0 07 Dec 2020
Accelerated Algorithms for Convex and Non-Convex Optimization on Manifolds Lizhen Lin B. Saparbayeva M. Zhang David B. Dunson 49 7 0 18 Oct 2020
Convergence Analysis of Riemannian Stochastic Approximation Schemes Alain Durmus P. Jiménez Eric Moulines Salem Said Hoi-To Wai 65 10 0 27 May 2020
Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold Bokun Wang Shiqian Ma Lingzhou Xue 83 19 0 03 May 2020
Physarum Powered Differentiable Linear Programming Layers and Applications Zihang Meng Sathya Ravi Vikas Singh 83 5 0 30 Apr 2020
Learning Polynomials of Few Relevant Dimensions Sitan Chen Raghu Meka 70 40 0 28 Apr 2020
From Nesterov's Estimate Sequence to Riemannian Acceleration Kwangjun Ahn S. Sra 97 78 0 24 Jan 2020
Gradient descent algorithms for Bures-Wasserstein barycenters Sinho Chewi Tyler Maunu Philippe Rigollet Austin J. Stromme 63 87 0 06 Jan 2020
Weakly Convex Optimization over Stiefel Manifold Using Riemannian Subgradient-Type Methods Xiao Li Shixiang Chen Zengde Deng Qing Qu Zhihui Zhu Anthony Man-Cho So 78 15 0 12 Nov 2019
Trivializations for Gradient-Based Optimization on Manifolds Mario Lezcano Casado 125 128 0 20 Sep 2019
Escaping from saddle points on Riemannian manifolds Yue Sun Nicolas Flammarion Maryam Fazel 64 73 0 18 Jun 2019
Rarely-switching linear bandits: optimization of causal effects for the real world B. Lansdell Sofia Triantafillou Konrad Paul Kording 55 4 0 30 May 2019
Wasserstein Style Transfer Youssef Mroueh OT 58 48 0 30 May 2019
Manifold Optimization Assisted Gaussian Variational Approximation Bingxin Zhou Junbin Gao Minh-Ngoc Tran Richard Gerlach 67 6 0 11 Feb 2019
Riemannian adaptive stochastic gradient algorithms on matrix manifolds Hiroyuki Kasai Pratik Jawanpuria Bamdev Mishra 84 3 0 04 Feb 2019