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cs.LG2024
Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction
Zhongxiang Fan, Zhaocheng Liu, Jian Liang +5
This paper investigates the one-epoch overfitting phenomenon in Click-Through Rate (CTR) models, where performance notably declines at the start of the second epoch. Despite extens…
cs.LG2023
Adaptive Neural Ranking Framework: Toward Maximized Business Goal for Cascade Ranking Systems
Yunli Wang, Zhiqiang Wang, Jian Yang +4
Cascade ranking is widely used for large-scale top-k selection problems in online advertising and recommendation systems, and learning-to-rank is an important way to optimize the m…