An in-depth study on adversarial learning-to-rank-Reference-Cited by-同舟云学术

An in-depth study on adversarial learning-to-rank

Published:2023-02-28 Issue:1-2 Volume:26 Page:
ISSN:1386-4564
Container-title:Information Retrieval Journal
language:en
Short-container-title:Inf Retrieval J

Author:

Yu Hai-Tao,Piryani Rajesh,Jatowt Adam,Inagaki Ryo,Joho Hideo,Kim Kyoung-Sook

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s10791-023-09419-0.pdf

Reference88 articles.

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2. Arjovsky, M., Chintala, S., & Bottou, L. (2017). (WGAN) Wasserstein generative adversarial network junhong huang. In ICML (pp. 1–44).

3. Bello, I., Kulkarni, S., Jain, S., Boutilier, C., Chi, E., Eban, E., & Meshi, O. (2019). Seq2Slate: Re-ranking and slate optimization with RNNs. In Proceedings of the workshop on negative dependence in machine learning.

4. Bradley, R.A., & Terry, M.E. (1952). Rank analysis of incomplete block designs: I. The method of paired comparisons. Biometrika, 39(34).

5. Bruch, S., Han, S., Bendersky, M., & Najork, M. (2020). A stochastic treatment of learning to rank scoring functions. In Proceedings of the 13th WSDM (pp. 61–69).

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