AdKDD 2024

Table of Contents

• PDF
  
• A Bag of Tricks for Scaling CPU-based Deep FFMs to more than 300m Predictions per Second PDF
  Adi Schwartz, Andraz Tori, Benjamin Ben-Shalom, Grega Gaspersic, Ramzi Hoseisi, Naama Ziporin, Davorin Kopic, Blaz Skrlj
• Augmented Two-Stage Bandit Framework: Practical Approaches for Improved Online Ad Selection PDF
  Hanxiao Wu, Seowon Han, Ryan Lakritz
• RankTower: A Synergistic Framework for Enhancing Two-Tower Pre-Ranking Model PDF
  Liubo Li, Yachen Yan
• Leveraging Instrumental Variables in Online Advertising Auctions : Robust Click-Through-Rate Prediction PDF
  Shinya Suzumura, Takahiro Hoshino, Ryohei Emori, Nobuyuki Shimizu
• SERP Interference Network and Its Applications in Search Advertising PDF
  Sandeep Appala, Purak Jain
• AFA: Auto-tuning Filters for Ads PDF
  Joobin Gharibshah, Abraham Bagherjeiran, Mahmuda Rahman
• Training Differentially Private Ad Prediction Models With Semi-Sensitive Features PDF
  Badih Ghazi, Ravi Kumar 0001, Pritish Kamath, Avinash V. Varadarajan, Steffen Rendle, Qiliang Cui, Charlie Harrison, Krishna Narra, Chiyuan Zhang, Nicolas Mayoraz, Lynn Chua, Pasin Manurangsi, Walid Krichene, Amer Sinha