PeerRank: Robust Learning to Rank With Peer Loss Over Noisy Labels
User-generated data are extensively utilized in learning to rank as they are easy to collect and up-to-date. However, the data inevitably contain noisy labels attributed to users’ annotation mistakes, lack of domain knowledge, system failure, etc., making building a robust model challenging....
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| Asıl Yazarlar: | , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
IEEE
2022-01-01
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| Seri Bilgileri: | IEEE Access |
| Konular: | |
| Online Erişim: | https://ieeexplore.ieee.org/document/9676597/ |
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