Ha QuangMinh ＨａＱｕａｎｇＭｉｎｈ

… Alternative Names

Ha Quang Minh Ha QuangMinh

Less

Researcher Number	90868928
Affiliation (Current)	2025: 国立研究開発法人理化学研究所, 革新知能統合研究センター, チームディレクター
Affiliation (based on the past Project Information) *help	2020 – 2022: 国立研究開発法人理化学研究所, 革新知能統合研究センター, ユニットリーダー
Review Section/Research Field	Principal Investigator Basic Section 61030:Intelligent informatics-related
Keywords	Principal Investigator Kernel methods / Hilbert space / Covariance operators / Riemannian manifolds / RKHS / Gaussian process / Hilbert manifold / Fisher-Rao metric / Information geometry / optimal transport … More / covariance operators / Functional data analysis / Optimal transport / Entropic regularization / Wasserstein distance / Divergences / Riemannian geometry / Information Geometry / Optimal Transport / Gaussian processes / Gaussian measures Less

Research Projects
(1 results)
Research Products
(7 results)

Machine learning and statistical methhods on infinite-dimensional manifoldsPrincipal Investigator
- Principal Investigator
  
  Ha Quang Minh
- Project Period (FY)
  2020 – 2022
- Research Category
  
  Grant-in-Aid for Scientific Research (B)
- Review Section
  
  Basic Section 61030:Intelligent informatics-related
- Research Institution
  Institute of Physical and Chemical Research

All 2023 2022 2021

All Journal Article Presentation

[Journal Article] Convergence and finite sample approximations of entropic regularized Wasserstein distances in Gaussian and RKHS settings2023
- Author(s)
  Ha Quang Minh
- Journal Title
  
  Analysis and Applications
  
  Volume: 21 Issue: 03 Pages: 719-775
- DOI
  10.1142/s0219530522500142
- Peer Reviewed / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20H04250
[Journal Article] Entropic Regularization of Wasserstein Distance Between Infinite-Dimensional Gaussian Measures and Gaussian Processes2022
- Author(s)
  Ha Quang Minh
- Journal Title
  
  Journal of Theoretical Probability
  
  Volume: - Issue: 1 Pages: 201-296
- DOI
  10.1007/s10959-022-01165-1
- Peer Reviewed / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20H04250
[Journal Article] Finite Sample Approximations of Exact and Entropic Wasserstein Distances Between Covariance Operators and Gaussian Processes2022
- Author(s)
  Ha Quang Minh
- Journal Title
  
  SIAM/ASA Journal on Uncertainty Quantification
  
  Volume: 10 Issue: 1 Pages: 96-124
- DOI
  10.1137/21m1410488
- Peer Reviewed / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20H04250
[Presentation] Fisher-Rao Riemannian geometry of equivalent Gaussian measures on Hilbert space2023
- Author(s)
  Ha Quang Minh
- Organizer
  6th International Conference on Geometric Science of Information
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20H04250
[Presentation] Renyi divergences in RKHS and Gaussian process settings2022
- Author(s)
  Ha Quang Minh
- Organizer
  International Conference on Information Geometry for Data Science
- Invited
- Data Source
  KAKENHI-PROJECT-20H04250
[Presentation] Riemannian distances between infinite-dimensional covariance operators and Gaussian processes2021
- Author(s)
  Ha Quang Minh
- Organizer
  4th International Conference on Econometrics and Statistics
- Invited / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20H04250
[Presentation] Regularized information geometric and optimal transport distances between covariance operators and Gaussian processes2021
- Author(s)
  Ha Quang Minh
- Organizer
  Conference on Mathematics of Machine Learning
- Invited / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20H04250

Ha QuangMinh Ｈａ ＱｕａｎｇＭｉｎｈ

Ha Quang Minh Ha QuangMinh

Research Projects

Research Products

Machine learning and statistical methhods on infinite-dimensional manifoldsPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Journal Article] Convergence and finite sample approximations of entropic regularized Wasserstein distances in Gaussian and RKHS settings2023

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Entropic Regularization of Wasserstein Distance Between Infinite-Dimensional Gaussian Measures and Gaussian Processes2022

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Finite Sample Approximations of Exact and Entropic Wasserstein Distances Between Covariance Operators and Gaussian Processes2022

Author(s)

Journal Title

DOI

Data Source

[Presentation] Fisher-Rao Riemannian geometry of equivalent Gaussian measures on Hilbert space2023

Author(s)

Organizer

Data Source

[Presentation] Renyi divergences in RKHS and Gaussian process settings2022

Author(s)

Organizer

Data Source

[Presentation] Riemannian distances between infinite-dimensional covariance operators and Gaussian processes2021

Author(s)

Organizer

Data Source

[Presentation] Regularized information geometric and optimal transport distances between covariance operators and Gaussian processes2021

Author(s)

Organizer

Data Source

Ha QuangMinh ＨａＱｕａｎｇＭｉｎｈ