Collaborative Filtering with Low Regret
© 2016 ACM. There is much empirical evidence that item-item collaborative filtering works well in practice. Motivated to understand this, we provide a framework to design and analyze various recommendation algorithms. The setup amounts to online binary matrix completion, where at each time a random...
| Main Authors: | , , |
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| Other Authors: | , , |
| Format: | Article |
| Language: | English |
| Published: |
Association for Computing Machinery (ACM),
2021-11-04T19:03:28Z.
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| Subjects: | |
| Online Access: | Get fulltext |