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Jul 2026
Partial Label Learning-Inspired Denoising Implicit Feedback for Recommendation
This work is the first to reformulate the recommendation denoising problem into a Partial Label Learning (PLL) task, and innovatively leverages PLL paradigms to directly resolve ambiguous implicit feedback, effectively recovering clean signals from noisy candidate sets.
Huilin Chen, Jie Lu, Kezhi Lu et al.
· Annual International ACM SIG... · 0 citations