Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods

20 May 2016

Mehrtash Harandi

Papers citing "Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods"

50 / 50 papers shown

Title
MPEC: Manifold-Preserved EEG Classification via an Ensemble of Clustering-Based Classifiers Shermin Shahbazi Mohammad-Reza Nasiri Majid Ramezani 118 0 0 30 Apr 2025
SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges Ce Ju Reinmar J. Kobler Antoine Collas M. Kawanabe Cuntai Guan Bertrand Thirion 104 0 0 26 Apr 2025
Nested subspace learning with flags Tom Szwagier Xavier Pennec 106 1 0 09 Feb 2025
Wasserstein Distance Rivals Kullback-Leibler Divergence for Knowledge Distillation Jiaming Lv Haoyuan Yang P. Li 154 2 0 11 Dec 2024
Product Geometries on Cholesky Manifolds with Applications to SPD Manifolds Ziheng Chen Yue Song Xiao-Jun Wu N. Sebe 84 2 0 02 Jul 2024
Matrix Manifold Neural Networks++ Xuan Son Nguyen Shuo Yang A. Histace 76 6 0 29 May 2024
A Framework for Bilevel Optimization on Riemannian Manifolds Andi Han Bamdev Mishra Pratik Jawanpuria Akiko Takeda 81 5 0 06 Feb 2024
Riemannian Self-Attention Mechanism for SPD Networks Rui Wang Xiao-Jun Wu Hui Li Josef Kittler 55 1 0 28 Nov 2023
Local Spherical Harmonics Improve Skeleton-Based Hand Action Recognition Katharina Prasse Steffen Jung Yuxuan Zhou Margret Keuper 64 1 0 21 Aug 2023
Riemannian Multinomial Logistics Regression for SPD Neural Networks Ziheng Chen Yue Song Gaowen Liu Ramana Rao Kompella Xiaojun Wu N. Sebe 80 5 0 18 May 2023
Building Neural Networks on Matrix Manifolds: A Gyrovector Space Approach X. Nguyen Shuo Yang 60 11 0 08 May 2023
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals Clément Bonet Benoit Malézieux A. Rakotomamonjy Lucas Drumetz Thomas Moreau M. Kowalski Nicolas Courty 96 16 0 10 Mar 2023
DreamNet: A Deep Riemannian Network based on SPD Manifold Learning for Visual Classification Rui Wang Xiaojun Wu Ziheng Chen Tianyang Xu J. Kittler 42 2 0 16 Jun 2022
First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces Michael I. Jordan Tianyi Lin Emmanouil-Vasileios Vlatakis-Gkaragkounis 66 19 0 04 Jun 2022
Discriminative Supervised Subspace Learning for Cross-modal Retrieval Haoming Zhang Xiaojun Wu Tianyang Xu Dongling Zhang 22 0 0 26 Jan 2022
Riemannian Local Mechanism for SPD Neural Networks Ziheng Chen Tianyang Xu Xiaojun Wu Rui Wang Zhiwu Huang J. Kittler 98 17 0 25 Jan 2022
Collaborative Representation for SPD Matrices with Application to Image-Set Classification Li-li Chu Rui Wang Xiaojun Wu 46 1 0 22 Jan 2022
Nested Hyperbolic Spaces for Dimensionality Reduction and Hyperbolic NN Design Xiran Fan Chun-Hao Yang B. Vemuri 88 18 0 03 Dec 2021
Temporal-attentive Covariance Pooling Networks for Video Recognition Zilin Gao Qilong Wang Bingbing Zhang Q. Hu P. Li 100 25 0 27 Oct 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
Learning Chebyshev Basis in Graph Convolutional Networks for Skeleton-based Action Recognition H. Sahbi GNN 59 0 0 12 Apr 2021
Discriminative Noise Robust Sparse Orthogonal Label Regression-based Domain Adaptation Lingkun Luo Liming Chen Shiqiang Hu OOD 59 6 0 09 Jan 2021
Nested Grassmannians for Dimensionality Reduction with Applications Chun-Hao Yang B. Vemuri 18 2 0 27 Oct 2020
Neural Architecture Search of SPD Manifold Networks R. Sukthanker Zhiwu Huang Suryansh Kumar Erik Goron Endsjo Yan Wu Luc Van Gool 110 14 0 27 Oct 2020
High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds Noémie Jaquier Leonel Rozo 103 24 0 21 Oct 2020
Stochastic Zeroth-order Riemannian Derivative Estimation and Optimization Jiaxiang Li Krishnakumar Balasubramanian Shiqian Ma 16 5 0 25 Mar 2020
Tangent space spatial filters for interpretable and efficient Riemannian classification Jiachen Xu Moritz Grosse-Wentrup V. Jayaram 46 16 0 23 Sep 2019
More About Covariance Descriptors for Image Set Coding: Log-Euclidean Framework based Kernel Matrix Representation Kaixuan Chen Xiaojun Wu Jieyi Ren Rui Wang J. Kittler 23 6 0 16 Sep 2019
Multiple Riemannian Manifold-valued Descriptors based Image Set Classification with Multi-Kernel Metric Learning Rui Wang Xiaojun Wu J. Kittler 35 30 0 06 Aug 2019
Hallucinating IDT Descriptors and I3D Optical Flow Features for Action Recognition with CNNs Lei Wang Piotr Koniusz D. Huynh 32 7 0 13 Jun 2019
Manifold-regression to predict from MEG/EEG brain signals without source modeling D. Sabbagh Pierre Ablin Gaël Varoquaux Alexandre Gramfort Denis A. Engemann 63 59 0 04 Jun 2019
A neural network based on SPD manifold learning for skeleton-based hand gesture recognition X. Nguyen Luc Brun O. Lézoray Sébastien Bougleux 3DH 77 119 0 29 Apr 2019
Analyzing Dynamical Brain Functional Connectivity As Trajectories on Space of Covariance Matrices Mengyu Dai Zhengwu Zhang Anuj Srivastava 50 32 0 10 Apr 2019
Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold Hiroyuki Kasai Bamdev Mishra 23 1 0 11 Feb 2019
Riemannian adaptive stochastic gradient algorithms on matrix manifolds Hiroyuki Kasai Pratik Jawanpuria Bamdev Mishra 84 3 0 04 Feb 2019
LGLG-WPCA: An Effective Texture-based Method for Face Recognition Chaorong Li Wei Huang Huafu Chen CVBM 21 0 0 20 Nov 2018
Perceptual Visual Interactive Learning Sheng-lan Liu Xiang Liu Yang Liu Lin Feng Hong Qiao Jian Zhou Yang Wang 23 4 0 25 Oct 2018
A Supervised Geometry-Aware Mapping Approach for Classification of Hyperspectral Images Ramanarayan Mohanty S. Happy Aurobinda Routray 18 0 0 07 Jul 2018
Grassmannian Discriminant Maps (GDM) for Manifold Dimensionality Reduction with Application to Image Set Classification Rui Wang Xiaojun Wu Kai-Xuan Chen J. Kittler 21 0 0 28 Jun 2018
Component SPD Matrices: A lower-dimensional discriminative data descriptor for image set classification Kai-Xuan Chen Xiao-Jun Wu 15 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 20 10 0 16 Jun 2018
Multiple Manifolds Metric Learning with Application to Image Set Classification Rui Wang Xiaojun Wu Kaixuan Chen J. Kittler 31 21 0 30 May 2018
A Simple Riemannian Manifold Network for Image Set Classification Rui Wang Xiaojun Wu J. Kittler 32 3 0 27 May 2018
Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders F. Bianchi L. Livi Karl Øyvind Mikalsen Michael C. Kampffmeyer Robert Jenssen AI4TS 84 11 0 09 May 2018
Learning a Robust Representation via a Deep Network on Symmetric Positive Definite Manifolds Zhi Gao Yuwei Wu Xingyuan Bu Yunde Jia 95 32 0 17 Nov 2017
Dimensionality Reduction on Grassmannian via Riemannian Optimization: A Generalized Perspective Tianci Liu Zelin Shi Yunpeng Liu 19 0 0 17 Nov 2017
Hierarchical Gaussian Descriptors with Application to Person Re-Identification Tetsu Matsukawa Takahiro Okabe Einoshin Suzuki Yoichi Sato 72 34 0 14 Jun 2017
A Riemannian gossip approach to subspace learning on Grassmann manifold Bamdev Mishra Hiroyuki Kasai Pratik Jawanpuria Atul Saroop 25 1 0 01 May 2017
Learning an Invariant Hilbert Space for Domain Adaptation Samitha Herath Mehrtash Harandi Fatih Porikli 104 107 0 25 Nov 2016
Geometry-aware Similarity Learning on SPD Manifolds for Visual Recognition Zhiwu Huang Ruiping Wang Xianqiu Li Wenxian Liu Shiguang Shan Luc Van Gool Xilin Chen 73 38 0 17 Aug 2016