D2K: Turning Historical Data into Retrievable Knowledge for Recommender Systems
A vast amount of user behavior data is constantly accumulating on today's large
recommendation platforms, recording users' various interests and tastes. Preserving …
recommendation platforms, recording users' various interests and tastes. Preserving …
Personalized Negative Reservoir for Incremental Learning in Recommender Systems
Recommender systems have become an integral part of online platforms. Every day the
volume of training data is expanding and the number of user interactions is constantly …
volume of training data is expanding and the number of user interactions is constantly …
Continual Collaborative Distillation for Recommender System
Knowledge distillation (KD) has emerged as a promising technique for addressing the
computational challenges associated with deploying large-scale recommender systems. KD …
computational challenges associated with deploying large-scale recommender systems. KD …