Salem Said

Orcid: 0000-0002-8067-1001

According to our database1, Salem Said authored at least 47 papers between 2007 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Subscripto multiplex: A Riemannian symmetric positive definite strategy for offline signature verification.
Pattern Recognit. Lett., March, 2023

Riemannian Statistics Meets Random Matrix Theory: Toward Learning From High-Dimensional Covariance Matrices.
IEEE Trans. Inf. Theory, 2023

Invariant kernels on Riemannian symmetric spaces: a harmonic-analytic approach.
CoRR, 2023

Geometric Learning with Positively Decomposable Kernels.
CoRR, 2023

Determinantal Expressions of Certain Integrals on Symmetric Spaces.
Proceedings of the Geometric Science of Information - 6th International Conference, 2023

2022
Riemannian information gradient methods for the parameter estimation of ECD.
Signal Process., 2022

Geometric Learning of Hidden Markov Models via a Method of Moments Algorithm.
CoRR, 2022

2021
Online Learning of Riemannian Hidden Markov Models in Homogeneous Hadamard Spaces.
Proceedings of the Geometric Science of Information - 5th International Conference, 2021

From Bayesian Inference to MCMC and Convex Optimisation in Hadamard Manifolds.
Proceedings of the Geometric Science of Information - 5th International Conference, 2021

Gaussian Distributions on Riemannian Symmetric Spaces in the Large N Limit.
Proceedings of the Geometric Science of Information - 5th International Conference, 2021

On Riemannian Stochastic Approximation Schemes with Fixed Step-Size.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Riemannian geometry for compound Gaussian distributions: Application to recursive change detection.
Signal Process., 2020

Convergence Analysis of Riemannian Stochastic Approximation Schemes.
CoRR, 2020

2019
Fast, Asymptotically Efficient, Recursive Estimation in a Riemannian Manifold.
Entropy, 2019

The Riemannian Barycentre as a Proxy for Global Optimisation.
Proceedings of the Geometric Science of Information - 4th International Conference, 2019

Online estimation of MGGD: the Riemannian Averaged Natural Gradient method.
Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2019

2018
Gaussian Distributions on Riemannian Symmetric Spaces: Statistical Learning With Structured Covariance Matrices.
IEEE Trans. Inf. Theory, 2018

Transfer Learning: A Riemannian Geometry Framework With Applications to Brain-Computer Interfaces.
IEEE Trans. Biomed. Eng., 2018

Fisher Vector Coding for Covariance Matrix Descriptors Based on the Log-Euclidean and Affine Invariant Riemannian Metrics.
J. Imaging, 2018

Covariance Matrices Encoding Based on the Log-Euclidean and Affine Invariant Riemannian Metrics.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

2017
Riemannian Gaussian Distributions on the Space of Symmetric Positive Definite Matrices.
IEEE Trans. Inf. Theory, 2017

Structure Tensor Riemannian Statistical Models for CBIR and Classification of Remote Sensing Images.
IEEE Trans. Geosci. Remote. Sens., 2017

Classification approach based on the product of riemannian manifolds from Gaussian parametrization space.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

A geometric learning approach on the space of complex covariance matrices.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Riemannian Online Algorithms for Estimating Mixture Model Parameters.
Proceedings of the Geometric Science of Information - Third International Conference, 2017

Riemannian Gaussian Distributions on the Space of Positive-Definite Quaternion Matrices.
Proceedings of the Geometric Science of Information - Third International Conference, 2017

Warped Metrics for Location-Scale Models.
Proceedings of the Geometric Science of Information - Third International Conference, 2017

Co-occurrence Matrix of Covariance Matrices: A Novel Coding Model for the Classification of Texture Images.
Proceedings of the Geometric Science of Information - Third International Conference, 2017

Maximum Likelihood Estimators on Manifolds.
Proceedings of the Geometric Science of Information - Third International Conference, 2017

Stochastic EM algorithm for mixture estimation on manifolds.
Proceedings of the 2017 IEEE 7th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, 2017

2016
Filtering from observations on Stiefel manifolds.
Signal Process., 2016

Riemannian Laplace Distribution on the Space of Symmetric Positive Definite Matrices.
Entropy, 2016

Parameters estimate of Riemannian Gaussian distribution in the manifold of covariance matrices.
Proceedings of the 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 2016

An M-estimator for robust centroid estimation on the manifold of covariance matrices: Performance analysis and application to image classification.
Proceedings of the 24th European Signal Processing Conference, 2016

2015
A New Riemannian Averaged Fixed-Point Algorithm for MGGD Parameter Estimation.
IEEE Signal Process. Lett., 2015

Texture classification using Rao's distance: An EM algorithm on the poincaré half plane.
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

Particle filtering with observations in a manifold.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Texture Classification Using Rao's Distance on the Space of Covariance Matrices.
Proceedings of the Geometric Science of Information - Second International Conference, 2015

2014
New Riemannian Priors on the Univariate Normal Model.
Entropy, 2014

Monte-carlo estimation from observation on stiefel manifold.
Proceedings of the IEEE International Conference on Acoustics, 2014

2013
Stationary Random Fields Arising From Second-Order Partial Differential Equations on Compact Lie Groups.
IEEE Trans. Inf. Theory, 2013

On Filtering with Observation in a Manifold: Reduction to a Classical Filtering Problem.
SIAM J. Control. Optim., 2013

2012
Extrinsic Mean of Brownian Distributions on Compact Lie Groups.
IEEE Trans. Inf. Theory, 2012

2010
Decompounding on compact lie groups.
IEEE Trans. Inf. Theory, 2010

2009
Nonparametric estimation for compound poisson processes on compact Lie groups.
Proceedings of the IEEE International Conference on Acoustics, 2009

2008
Fast Complexified Quaternion Fourier Transform.
IEEE Trans. Signal Process., 2008

2007
Exact Principal Geodesic Analysis for data on SO(3).
Proceedings of the 15th European Signal Processing Conference, 2007


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