Abstract is missing.
- RecSys Challenge 2023 Dataset: Ads Recommendations in Online AdvertisingRahul Agrawal, Sarang Brahme, Sourav Maitra, Abhishek Srivastava 0004, Athirai A. Irissappane, Yong Liu 0020, Saikishore Kalloori. 1-3 [doi]
- Integrating Explicit and Implicit Feature Interactions for Online Ad Installation ForecastingJiawei Jiang, Bing Wang, Jingyuan Wang. 4-8 [doi]
- Lightweight Boosting Models for User Response Prediction Using Adversarial ValidationHyeonwoo Kim, Wonsung Lee. 9-13 [doi]
- A Simple and Robust Ensemble For Click-Through Rate PredictionXingmei Wang, Yankai Wang, Defu Lian. 14-17 [doi]
- Large Scale CVR Prediction through Hierarchical History ModelingQi Zhang, Zhibin Zhang, Biao Lu, Bangzheng He, Liangbi Li, Zhenhua Dong. 18-22 [doi]
- Robust User Engagement Modeling With Transformers and Self SupervisionYichao Lu, Maksims Volkovs. 23-27 [doi]
- Capturing Performance and Privacy by Assembling Avengers of Online AdvertisingTaehee Kim, Seungyun Baek, Taehyeon Jeon, Hojin Jung, Joonhong Kim, Taeho Lee. 28-32 [doi]
- Pessimistic Rescaling and Distribution Shift of Boosting Models for Impression-Aware Online Advertising RecommendationPaolo Basso, Arturo Benedetti, Nicola Cecere, Alessandro Maranelli, Salvatore Marragony, Samuele Peri, Andrea Riboni, Alessandro Verosimile, Davide Zanutto, Maurizio Ferrari Dacrema. 33-38 [doi]
- A Simple yet Strong Approach for Installation Prediction in ShareChat AdsXiaoteng Shen, LiangCai Su, Zhutian Lin, Xiao Xi. 39-43 [doi]
- Graph Enhanced Feature Engineering for Privacy Preserving Recommendation SystemsChendi Xue, Xinyao Wang, Yu Zhou, Poovaiah M. Palangappa, Rita Brugarolas Brufau, Aasavari Dhananjay Kakne, Ravi Motwani, Ke Ding, Jian Zhang. 44-51 [doi]