Computable PAC Learning of Continuous Features-Reference-Cited by-同舟云学术

Computable PAC Learning of Continuous Features

Published:2022-08-02 Issue: Volume: Page:
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Container-title:Proceedings of the 37th Annual ACM/IEEE Symposium on Logic in Computer Science
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Author:

Ackerman Nathanael¹,Asilis Julian²,Di Jieqi²,Freer Cameron³,Tristan Jean-Baptiste²

Affiliation:

1. Harvard University, USA

2. Boston College, USA

3. Massachusetts Institute of Technology, USA

Funder

National Science Foundation

Intel Probabilistic Computing Center

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3531130.3533330

Reference20 articles.

1. Nathanael Ackerman Julian Asilis Jieqi Di Cameron Freer and Jean-Baptiste Tristan. 2021. On Computable Learning of Continuous Features. arXiv e-print 2111.14630(2021). arXiv:2111.14630 Nathanael Ackerman Julian Asilis Jieqi Di Cameron Freer and Jean-Baptiste Tristan. 2021. On Computable Learning of Continuous Features. arXiv e-print 2111.14630(2021). arXiv:2111.14630

2. Nathanael Ackerman , Julian Asilis , Jieqi Di , Cameron Freer , and Jean-Baptiste Tristan . 2021 . On the Computable Learning of Continuous Features. In Eighteenth International Conference on Computability and Complexity in Analysis. http://cca-net.de/cca2021/ Nathanael Ackerman, Julian Asilis, Jieqi Di, Cameron Freer, and Jean-Baptiste Tristan. 2021. On the Computable Learning of Continuous Features. In Eighteenth International Conference on Computability and Complexity in Analysis. http://cca-net.de/cca2021/

3. Sushant Agarwal , Nivasini Ananthakrishnan , Shai Ben-David , Tosca Lechner , and Ruth Urner . 2020 . On Learnability with Computable Learners . In Proceedings of the 31st International Conference on Algorithmic Learning Theory (ALT)(PMLR, Vol. 117) . 48–60. http://proceedings.mlr.press/v117/agarwal20b.html Sushant Agarwal, Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner, and Ruth Urner. 2020. On Learnability with Computable Learners. In Proceedings of the 31st International Conference on Algorithmic Learning Theory (ALT)(PMLR, Vol. 117). 48–60. http://proceedings.mlr.press/v117/agarwal20b.html

4. LEARNING THEORY IN THE ARITHMETIC HIERARCHY

5. Learnability and the Vapnik-Chervonenkis dimension

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