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cs.LG2025★ 1 cited
MCNet: Monotonic Calibration Networks for Expressive Uncertainty Calibration in Online Advertising
Quanyu Dai, Jiaren Xiao, Zhaocheng Du +4
In online advertising, uncertainty calibration aims to adjust a ranking model's probability predictions to better approximate the true likelihood of an event, e.g., a click or a co…
cs.LG2024
Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning
Yuankai Luo, Hongkang Li, Qijiong Liu +2
We present a novel end-to-end framework that generates highly compact (typically 6-15 dimensions), discrete (int4 type), and interpretable node representations, termed node identif…