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Click Through Rate Prediction On Kdd12

Metrics

AUC
Log Loss

Results

Performance results of various models on this benchmark

Paper Title
DCNv30.80980.1494FCN: Fusing Exponential and Linear Cross Network for Click-Through Rate Prediction
MemoNet0.8060-MemoNet: Memorizing All Cross Features' Representations Efficiently via Multi-Hash Codebook Network for CTR Prediction
OptEmbed0.80280.1521OptEmbed: Learning Optimal Embedding Table for Click-through Rate Prediction
OptFS0.79880.1527Optimizing Feature Set for Click-Through Rate Prediction
AutoInt0.78810.1545AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
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