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Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices

10 July 2015

Papers citing "Riemannian Dictionary Learning and Sparse Coding for Positive Definite Matrices"

36 / 36 papers shown

Title
A Novel Riemannian Sparse Representation Learning Network for Polarimetric SAR Image Classification Junfei Shi Mengmeng Nie Weisi Lin Haiyan Jin Junlong Li Rui Wang 75 0 0 24 Feb 2025
Streamlining in the Riemannian Realm: Efficient Riemannian Optimization with Loopless Variance Reduction Yury Demidovich Grigory Malinovsky Peter Richtárik 88 3 0 11 Mar 2024
Riemannian Complex Matrix Convolution Network for PolSAR Image Classification Junfei Shi Wei Wang Haiyan Jin Mengmeng Nie Shanshan Ji 15 1 0 06 Dec 2023
Differential geometry with extreme eigenvalues in the positive semidefinite cone Cyrus Mostajeran Nathael Da Costa Graham W. Van Goffrier R. Sepulchre 70 4 0 14 Apr 2023
Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning Wu Lin Valentin Duruisseaux Melvin Leok Frank Nielsen Mohammad Emtiyaz Khan Mark Schmidt 104 10 0 20 Feb 2023
A numerical approximation method for the Fisher-Rao distance between multivariate normal distributions Frank Nielsen 51 19 0 16 Feb 2023
Accelerated Riemannian Optimization: Handling Constraints with a Prox to Bound Geometric Penalties David Martínez-Rubio Sebastian Pokutta 78 10 0 26 Nov 2022
A Riemannian ADMM Jiaxiang Li Shiqian Ma Tejes Srivastava 43 17 0 03 Nov 2022
Geometric Sparse Coding in Wasserstein Space M. Mueller Shuchin Aeron James M. Murphy Abiy Tasissa 48 4 0 21 Oct 2022
Riemannian accelerated gradient methods via extrapolation Andi Han Bamdev Mishra Pratik Jawanpuria Junbin Gao 68 10 0 13 Aug 2022
Riemannian Nearest-Regularized Subspace Classification for Polarimetric SAR images Junfei Shi Haiyan Jin 26 10 0 02 Jan 2022
Learning with symmetric positive definite matrices via generalized Bures-Wasserstein geometry Andi Han Bamdev Mishra Pratik Jawanpuria Junbin Gao 50 5 0 20 Oct 2021
Reconciliation of Statistical and Spatial Sparsity For Robust Image and Image-Set Classification Hao Cheng Kim-Hui Yap Bihan Wen 44 0 0 01 Jun 2021
Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence Yuetian Luo Anru R. Zhang 157 20 0 24 Apr 2021
Accurate and fast matrix factorization for low-rank learning R. Godaz R. Monsefi F. Toutounian Reshad Hosseini 11 0 0 21 Apr 2021
Learning Log-Determinant Divergences for Positive Definite Matrices A. Cherian P. Stanitsas Jue Wang Mehrtash Harandi V. Morellas Nikolaos Papanikolopoulos 38 4 0 13 Apr 2021
No-go Theorem for Acceleration in the Hyperbolic Plane Linus Hamilton Ankur Moitra 60 21 0 14 Jan 2021
Global Riemannian Acceleration in Hyperbolic and Spherical Spaces David Martínez-Rubio 123 20 0 07 Dec 2020
A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis Zhongruo Wang Bingyuan Liu Shixiang Chen Shiqian Ma Lingzhou Xue Hongyu Zhao 54 22 0 18 Jul 2020
Dual-level Semantic Transfer Deep Hashing for Efficient Social Image Retrieval Lei Zhu Hui Cui Zhiyong Cheng Jingjing Li Zheng Zhang 53 29 0 10 Jun 2020
A Riemannian Primal-dual Algorithm Based on Proximal Operator and its Application in Metric Learning Shijun Wang Baocheng Zhu Lintao Ma Yuan Qi 32 0 0 19 May 2020
Stochastic Zeroth-order Riemannian Derivative Estimation and Optimization Jiaxiang Li Krishnakumar Balasubramanian Shiqian Ma 16 5 0 25 Mar 2020
Sparse Coding of Shape Trajectories for Facial Expression and Action Recognition Amor Ben Tanfous Hassen Drira Boulbaba Ben Amor 3DH 57 30 0 08 Aug 2019
An Alternating Manifold Proximal Gradient Method for Sparse PCA and Sparse CCA Shixiang Chen Shiqian Ma Lingzhou Xue H. Zou 56 13 0 27 Mar 2019
Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold Hiroyuki Kasai Bamdev Mishra 23 1 0 11 Feb 2019
Manifold Optimization Assisted Gaussian Variational Approximation Bingxin Zhou Junbin Gao Minh-Ngoc Tran Richard Gerlach 67 6 0 11 Feb 2019
R-SPIDER: A Fast Riemannian Stochastic Optimization Algorithm with Curvature Independent Rate J.N. Zhang Hongyi Zhang S. Sra 76 39 0 10 Nov 2018
Proximal Gradient Method for Nonsmooth Optimization over the Stiefel Manifold Shixiang Chen Shiqian Ma Anthony Man-Cho So Tong Zhang 112 15 0 02 Nov 2018
Riemannian Adaptive Optimization Methods Gary Bécigneul O. Ganea ODL 128 259 0 01 Oct 2018
Energy Disaggregation via Deep Temporal Dictionary Learning Mahdi Khodayar Jianhui Wang Zhaoyu Wang 36 67 0 10 Sep 2018
Component SPD Matrices: A lower-dimensional discriminative data descriptor for image set classification Kai-Xuan Chen Xiao-Jun Wu 17 15 0 16 Jun 2018
Riemannian kernel based Nyström method for approximate infinite-dimensional covariance descriptors with application to image set classification Kaixuan Chen Xiaojun Wu Rui Wang J. Kittler 22 10 0 16 Jun 2018
Riemannian Optimization via Frank-Wolfe Methods Melanie Weber S. Sra 69 33 0 30 Oct 2017
Learning Discriminative Alpha-Beta-divergence for Positive Definite Matrices (Extended Version) A. Cherian P. Stanitsas Mehrtash Harandi V. Morellas Nikolaos Papanikolopoulos 41 2 0 05 Aug 2017
Multivariate Regression with Gross Errors on Manifold-valued Data Xiaowei Zhang Xudong Shi Yu Sun Li Cheng 45 8 0 26 Mar 2017
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds Hongyi Zhang Sashank J. Reddi S. Sra 117 241 0 23 May 2016