Scalable Model-Free Feature Screening via Sliced-Wasserstein Dependency-Reference-Cited by-同舟云学术

Scalable Model-Free Feature Screening via Sliced-Wasserstein Dependency

Published:2023-04-12 Issue:4 Volume:32 Page:1501-1511
ISSN:1061-8600
Container-title:Journal of Computational and Graphical Statistics
language:en
Short-container-title:Journal of Computational and Graphical Statistics

Author:

Li Tao¹,Yu Jun²^ORCID,Meng Cheng³^ORCID

Affiliation:

1. Institute of Statistics and Big Data, Renmin University of China, Beijing, China

2. School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, China

3. Center for Applied Statistics, Institute of Statistics and Big Data, Renmin University of China, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Discrete Mathematics and Combinatorics,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/10618600.2023.2183213

Reference67 articles.

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3. Belghazi, M. I., Baratin, A., Rajeshwar, S., Ozair, S., Bengio, Y., Courville, A., and Hjelm, D. (2018), “Mutual Information Neural Estimation,” in International Conference on Machine Learning, pp. 531–540. PMLR.

4. Sliced and Radon Wasserstein Barycenters of Measures

5. Carriere, M., Cuturi, M., and Oudot, S. (2017), “Sliced Wasserstein Kernel for Persistence Diagrams,” in International Conference on Machine Learning, pp. 664–673. PMLR.