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cs.IR2025
HyperZero: A Customized End-to-End Auto-Tuning System for Recommendation with Hourly Feedback
Xufeng Cai, Ziwei Guan, Lei Yuan +11
Modern recommendation systems can be broadly divided into two key stages: the ranking stage, where the system predicts various user engagements (e.g., click-through rate, like rate…
cs.IR2022★ 2 cited
LPFS: Learnable Polarizing Feature Selection for Click-Through Rate Prediction
Yi Guo, Zhaocheng Liu, Jianchao Tan +6
In industry, feature selection is a standard but necessary step to search for an optimal set of informative feature fields for efficient and effective training of deep Click-Throug…