Minh Ha Quang
Minh Ha Quang
Unit Leader, Functional Analytic Learning Unit, RIKEN Center for Advanced Intelligence Project
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Cited by
Cited by
Mercer’s theorem, feature maps, and smoothing
HQ Minh, P Niyogi, Y Yao
International Conference on Computational Learning Theory, 154-168, 2006
Some properties of Gaussian reproducing kernel Hilbert spaces and their implications for function approximation and learning theory
HQ Minh
Constructive Approximation 32 (2), 307-338, 2010
A new kernel-based approach for nonlinearsystem identification
G Pillonetto, MH Quang, A Chiuso
IEEE Transactions on Automatic Control 56 (12), 2825-2840, 2011
Log-Hilbert-Schmidt metric between positive definite operators on Hilbert spaces
M Ha Quang, M San Biagio, V Murino
Advances in neural information processing systems 27, 2014
Semi-supervised multi-feature learning for person re-identification
D Figueira, L Bazzani, HQ Minh, M Cristani, A Bernardino, V Murino
2013 10th IEEE international conference on advanced video and signal based …, 2013
A unifying framework for vector-valued manifold regularization and multi-view learning
MH Quang, L Bazzani, V Murino
International conference on machine learning, 100-108, 2013
A unifying framework in vector-valued reproducing kernel hilbert spaces for manifold regularization and co-regularized multi-view learning
HQ Minh, L Bazzani, V Murino
The Journal of Machine Learning Research 17 (1), 769-840, 2016
Image and video colorization using vector-valued reproducing kernel Hilbert spaces
M Ha Quang, SH Kang, TM Le
Journal of Mathematical Imaging and Vision 37 (1), 49-65, 2010
Scalable matrix-valued kernel learning for high-dimensional nonlinear multivariate regression and granger causality
V Sindhwani, MH Quang, AC Lozano
arXiv preprint arXiv:1210.4792, 2012
Vector-valued manifold regularization
HQ Minh, V Sindhwani
International Conference on Machine Learning, 2011
Kernel-based classification for brain connectivity graphs on the Riemannian manifold of positive definite matrices
L Dodero, HQ Minh, M San Biagio, V Murino, D Sona
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 42-45, 2015
Infinite-dimensional Log-Determinant divergences between positive definite trace class operators
HQ Minh
Linear Algebra and Its Applications 528, 331-383, 2017
Covariances in computer vision and machine learning
HQ Minh, V Murino
Synthesis Lectures on Computer Vision 7 (4), 1-170, 2017
Entropy-regularized 2-Wasserstein distance between Gaussian measures
A Mallasto, A Gerolin, HQ Minh
Information Geometry 5 (1), 289-323, 2022
Reproducing kernel Hilbert spaces in learning theory
HQ Minh
Approximate Log-Hilbert-Schmidt Distances Between Covariance Operators for Image Classification
HQ Minh, M San Biagio, L Bazzani, V Murino
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016
Trusting skype: Learning the way people chat for fast user recognition and verification
G Roffo, M Cristani, L Bazzani, H Minh, V Murino
Proceedings of the IEEE International Conference on Computer Vision …, 2013
Multivariate slow feature analysis and decorrelation filtering for blind source separation
HQ Minh, L Wiskott
IEEE transactions on image processing 22 (7), 2737-2750, 2013
Algorithmic advances in Riemannian geometry and applications
HQ Minh, V Murino, HQ Minh
Springer, 2016
A unified formulation for the Bures-Wasserstein and Log-Euclidean/Log-Hilbert-Schmidt distances between positive definite operators
HQ Minh
International Conference on Geometric Science of Information, 475-483, 2019
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