Recommendation Unlearning via Matrix Correction

no code implementations • 29 Jul 2023 • Jiahao Liu, Dongsheng Li, Hansu Gu, Tun Lu, Jiongran Wu, Peng Zhang, Li Shang, Ning Gu

We conducted comprehensive experiments to validate the effectiveness of IMCorrect and the results demonstrate that IMCorrect is superior in completeness, utility, and efficiency, and is applicable in many recommendation unlearning scenarios.

Collaborative Filtering Recommendation Systems