Light-FMP prunes features and model parameters in deep recommender systems by pretraining a hard-concrete masking layer on data subsets, then retraining the reduced model to improve both efficiency and accuracy over prior methods.
Measuring the business value of recommender systems.ACM Transactions on Management Information Systems (TMIS), 10(4):1–23,
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Light-FMP: Lightweight Feature and Model Pruning for Enhanced Deep Recommender Systems
Light-FMP prunes features and model parameters in deep recommender systems by pretraining a hard-concrete masking layer on data subsets, then retraining the reduced model to improve both efficiency and accuracy over prior methods.