Kavli Affiliate: Ke Wang | First 5 Authors: Yao Yao, Bin Liu, Haoxun He, Dakui Sheng, Ke Wang | Summary: Input features play a crucial role in the predictive performance of DNN-based industrial recommender systems with thousands of categorical and continuous fields from users, items, contexts, and their interactions. Noisy features and inappropriate embedding dimension […]
Continue.. i-Razor: A Neural Input Razor for Feature Selection and Dimension Search in Large-Scale Recommender Systems