Learning Product Rankings Robust to Fake Users

Bibliographic Details
Main Authors: Golrezaei, Negin, Manshadi, Vahideh, Schneider, Jon, Sekar, Shreyas
Other Authors: Sloan School of Management
Format: Article
Language:English
Published: ACM|Proceedings of the 22nd ACM Conference on Economics and Computation 2022
Online Access:https://hdl.handle.net/1721.1/145944
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author Golrezaei, Negin
Manshadi, Vahideh
Schneider, Jon
Sekar, Shreyas
author2 Sloan School of Management
author_facet Sloan School of Management
Golrezaei, Negin
Manshadi, Vahideh
Schneider, Jon
Sekar, Shreyas
author_sort Golrezaei, Negin
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institution Massachusetts Institute of Technology
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spelling mit-1721.1/1459442023-01-18T20:55:27Z Learning Product Rankings Robust to Fake Users Golrezaei, Negin Manshadi, Vahideh Schneider, Jon Sekar, Shreyas Sloan School of Management 2022-10-24T13:02:42Z 2022-10-24T13:02:42Z 2021-07-18 2022-10-19T16:02:45Z Article http://purl.org/eprint/type/ConferencePaper 978-1-4503-8554-1 https://hdl.handle.net/1721.1/145944 Golrezaei, Negin, Manshadi, Vahideh, Schneider, Jon and Sekar, Shreyas. 2021. "Learning Product Rankings Robust to Fake Users." PUBLISHER_POLICY en https://doi.org/10.1145/3465456.3467580 Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. The author(s) application/pdf ACM|Proceedings of the 22nd ACM Conference on Economics and Computation ACM|Proceedings of the 22nd ACM Conference on Economics and Computation
spellingShingle Golrezaei, Negin
Manshadi, Vahideh
Schneider, Jon
Sekar, Shreyas
Learning Product Rankings Robust to Fake Users
title Learning Product Rankings Robust to Fake Users
title_full Learning Product Rankings Robust to Fake Users
title_fullStr Learning Product Rankings Robust to Fake Users
title_full_unstemmed Learning Product Rankings Robust to Fake Users
title_short Learning Product Rankings Robust to Fake Users
title_sort learning product rankings robust to fake users
url https://hdl.handle.net/1721.1/145944
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