Machine Unlearning for Recommendation Systems: An Insight

Author:

Sachdeva Bhavika,Rathee Harshita,Sristi ,Sharma Arun,Wydmański Witold

Publisher

Springer Nature Singapore

Reference34 articles.

1. Covington P, Adams J, Sargin E (2016) Deep neural networks for Youtube recommendations. In: Proceedings of the 10th ACM conference on recommender systems, ser. RecSys ’16. Association for Computing Machinery, New York, NY, USA, pp 191–198. [Online]. Available: https://doi.org/10.1145/2959100.2959190

2. Ying R, He R, Chen K, Eksombatchai P, Hamilton WL, Leskovec J (2018) Graph convolutional neural networks for web-scale recommender systems. In: Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery data mining, ser. KDD ’18. Association for Computing Machinery, New York, NY, USA, pp 974–983. [Online]. Available: https://doi.org/10.1145/3219819.3219890

3. Xu M, Sun J, Yang X, Yao K, Wang C (2023) Netflix and forget: efficient and exact machine unlearning from bi-linear recommendations. [Online]. Available: https://arxiv.org/abs/2302.06676

4. Eksombatchai C, Jindal P, Liu JZ, Liu Y, Sharma R, Sugnet C, Ulrich M, Leskovec J (2017) Pixie: a system for recommending 3+ billion items to 200+ million users in real-time. [Online]. Available: https://arxiv.org/abs/1711.07601

5. Sekhari A, Acharya J, Kamath G, Suresh AT (2021) Remember what you want to forget: Algorithms for machine unlearning. ArXiv abs/2103.03279. [Online]. Available: https://api.semanticscholar.org/CorpusID:232134970

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