11 citations · 11 across the 4 of their papers we have counts for
4 papers
ROI-Constrained Bidding via Curriculum-Guided Bayesian Reinforcement Learning
Haozhe Wang, Chao Du, Panyan Fang +4
Real-Time Bidding (RTB) is an important mechanism in modern online advertising systems. Advertisers employ bidding strategies in RTB to optimize their advertising effects subject t…
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…
AMCAD: Adaptive Mixed-Curvature Representation based Advertisement Retrieval System
Zhirong Xu, Shiyang Wen, Junshan Wang +8
Graph embedding based retrieval has become one of the most popular techniques in the information retrieval community and search engine industry. The classical paradigm mainly relie…
ZOOMER: Boosting Retrieval on Web-scale Graphs by Regions of Interest
Yuezihan Jiang, Yu Cheng, Hanyu Zhao +6
We introduce ZOOMER, a system deployed at Taobao, the largest e-commerce platform in China, for training and serving GNN-based recommendations over web-scale graphs. ZOOMER is desi…