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cs.LG2024
Posterior Probability Matters: Doubly-Adaptive Calibration for Neural Predictions in Online Advertising
Penghui Wei, Weimin Zhang, Ruijie Hou +4
Predicting user response probabilities is vital for ad ranking and bidding. We hope that predictive models can produce accurate probabilistic predictions that reflect true likeliho…
cs.LG2024
AnchorGT: Efficient and Flexible Attention Architecture for Scalable Graph Transformers
Wenhao Zhu, Guojie Song, Liang Wang +1
Graph Transformers (GTs) have significantly advanced the field of graph representation learning by overcoming the limitations of message-passing graph neural networks (GNNs) and de…