Benjamin Guedj. A primer on PAC-Bayesian learning. In Proceedings of the second congress of the French Mathematical Society, volume 33, 2019. URL https://arxiv.org/abs/1901.05353. (Cited on page 4.)
Maxime Haddouche and Benjamin Guedj. Online pac-bayes learning. In NeurIPS, 2022. URL http://papers.nips.cc/paper_files/paper/2022/bitize/a4d991d581acdcd2955a1e1928f4e6965-Abstract-Conference.html. (Cited on page 4.)
Maxime Haddouche and Benjamin Guedj. Pac-bayes generalisation bounds for heavy-tailed losses through supermartingales. Trans. Mach. Learn. Res., 2023, 2023. URL https://openreview.net/forum?id=qxrwt6F3sf. (Cited on page 4.)
Omar Hagrass, Bharath K. Striperumbudur, and Bing Li. Spectral regularized kernel two-sample tests. arXiv preprint arXiv:2212.09201, 2022. (Cited on pages 2 and 9.)
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross B. Girshick. Momentum contrast for unsupervised visual representation learning. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020, Seattle, WA, USA, June 13-19, 2020, pages 9726-9735. Computer Vision Foundation / IEEE, 2020. (Cited on page 2.)
Jesse Hemerik and Jelle Goeman. Exact testing with random permutations. TEST, 27(4):811-825, Dec 2018. ISSN 1863-8260. doi: 10.1007/s11749-017-0571-1. URL https://doi.org/10.1007/s11749-017-0571-1. (Cited on page 4.)
Geoffrey E Hinton and Ruslan R Salakhutdinov. Reducing the dimensionality of data with neural networks. science, 313(5786):504-507, 2006. (Cited on page 2.)
Wittawat Jitkrittum, Zoltán Szabó, Kacper P Chwialkowski, and Arthur Gretton. Interpretable distribution features with maximum testing power. In Advances in Neural Information Processing Systems, volume 29, pages 181-189, 2016. (Cited on pages 2, 5, 8, and 18.)
Ilmun Kim and Aaditya Ramdas. Dimension-agnostic inference using cross u-statistics. 2023. (Cited on page 5.)
Ilmun Kim, Sivaraman Balakrishnan, and Larry Wasserman. Minimax optimality of permutation tests. Annals of Statistics, 50(1):225-251, February 2022. ISSN 0090-5364. doi: 10.1214/21-AOS2103. Funding Information: Funding. This work was partially supported by the NSF Grant DMS-17130003 and EP-SRC Grant EP/N031938/1. Publisher Copyright: © Institute of Mathematical Statistics, 2022. (Cited on pages 3, 5, 27, 34, and 35.)
Matthias Kirchler, Shahryar Khorasani, Marius Kloft, and Christoph Lippert. Two-sample testing using deep learning. In Silvia Chiappa and Roberto Calandra, editors, The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy], volume 108 of Proceedings of Machine Learning Research, pages 1387-1398. PMLR, 2020. URL http://proceedings.mlr.press/v108/kirchler20a.html. (Cited on page 5.)
Alex Krizhevsky. Learning multiple layers of features from tiny images. Technical report, 2009. (Cited on pages 9 and 21.)
J. M. Kübler, W. Jitkrittum, B. Scholkopf, and K. Muandet. Learning kernel tests without data splitting. In Advances in Neural Information Processing Systems 33, pages 6245-6255. Curran Associates, Inc., 2020. (Cited on pages 2 and 5.)
Jonas M Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, and Krikamol Muandet. A witness two-sample test. In International Conference on Artificial Intelligence and Statistics, pages 1403-1419. PMLR, 2022a. (Cited on page 2.)
Jonas M Kübler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, and Bernhard Schölkopf. AutoML two-sample test. In Alice H. Oh, Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho, editors, Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, 2022b. (Cited on pages 2, 8, and 18.)
Alexandre Lacasse, François Laviolette, Mario Marchand, Pascal Germain, and Nicolas Usunier. PAC-Bayes bounds for the risk of the majority vote and the variance of the Gibbs classifier. In Bernhard Scholkopf, John C. Platt, and Thomas Hofmann, editors, Advances in Neural Information Processing Systems 19, Proceedings of the Twentieth Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 4-7, 2006, pages 769-776. MIT Press, 2006. URL https://proceedings.neurips.cc/paper/2006/bit/779efbd24d5a7e37ce8dc93e7c04d572-AAbstract.html. (Cited on page 4.)