Building robust deep recommender systems: Utilizing a weighted adversarial noise propagation framework with robust fine-tuning modules
Abstract: Highlights•We propose RAWP-FT to boost model robustness while maintaining generalization.•RAWP-FT uses weight perturbations and robust fine-tuning to improve model robustness.•RAWP-FT tested on MLP enhances model robustness under adversarial conditions.
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