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cs.LG2025
Auto-bidding under Return-on-Spend Constraints with Uncertainty Quantification
Jiale Han, Chun Gan, Chengcheng Zhang +4
Auto-bidding systems are widely used in advertising to automatically determine bid values under constraints such as total budget and Return-on-Spend (RoS) targets. Existing works o…
cs.LG2025
Generative Modeling with Multi-Instance Reward Learning for E-commerce Creative Optimization
Qiaolei Gu, Yu Li, DingYi Zeng +6
In e-commerce advertising, selecting the most compelling combination of creative elements -- such as titles, images, and highlights -- is critical for capturing user attention and…
cs.LG2025
Generative Click-through Rate Prediction with Applications to Search Advertising
Lingwei Kong, Lu Wang, Changping Peng +3
Click-Through Rate (CTR) prediction models are integral to a myriad of industrial settings, such as personalized search advertising. Current methods typically involve feature extra…