| 2020 | Offline Contextual Multi-armed Bandits for Mobile Health Interventions: A Case Study on Emotion Regulation. | Mawulolo K. Ameko, Miranda L. Beltzer, Lihua Cai, Mehdi Boukhechba, Bethany A. Teachman, Laura E. Barnes |
| 2020 | The Effect of Personality Traits on Persuading Recommender System Users. | Alaa Alslaity, Thomas Tran |
| 2020 | Engaging with Tweets: The Missing Dataset On Social Media. | Seyed Ali Alhosseini, Raad Bin Tareaf, Christoph Meinel |
| 2020 | Making Sense of the Urban Future: Recommendation Systems in Smart Cities. | Dirk Ahlers |
| 2020 | Goal-driven Command Recommendations for Analysts. | Samarth Aggarwal, Rohin Garg, Abhilasha Sancheti, Bhanu Prakash Reddy Guda, Iftikhar Ahamath Burhanuddin |
| 2020 | Making Neural Networks Interpretable with Attribution: Application to Implicit Signals Prediction. | Darius Afchar, Romain Hennequin |
| 2020 | Workshop on Context-Aware Recommender Systems. | Gediminas Adomavicius, Konstantin Bauman, Bamshad Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger |
| 2020 | The Connection Between Popularity Bias, Calibration, and Fairness in Recommendation. | Himan Abdollahpouri, Masoud Mansoury, Robin Burke, Bamshad Mobasher |
| 2020 | FISSA: Fusing Item Similarity Models with Self-Attention Networks for Sequential Recommendation. | Jing Lin, Weike Pan, Zhong Ming |
| 2020 | Cascading Hybrid Bandits: Online Learning to Rank for Relevance and Diversity. | Chang Li, Haoyun Feng, Maarten de Rijke |
| 2020 | Building a reciprocal recommendation system at scale from scratch: Learnings from one of Japan's prominent dating applications. | R. Ramanathan, Nicolas K. Shinada, Sucheendra K. Palaniappan |
| 2019 | Recommender systems for contextually-aware, versioned items. | Yayu Zhou |
| 2019 | Multi-stakeholder recommendations: case studies, methods and challenges. | Yong Zheng |
| 2019 | From preference into decision making: modeling user interactions in recommender systems. | Qian Zhao, Martijn C. Willemsen, Gediminas Adomavicius, F. Maxwell Harper, Joseph A. Konstan |
| 2019 | Recommending what video to watch next: a multitask ranking system. | Zhe Zhao, Lichan Hong, Li Wei, Jilin Chen, Aniruddh Nath, Shawn Andrews, Aditee Kumthekar, Maheswaran Sathiamoorthy, Xinyang Yi, Ed H. Chi |
| 2019 | Incorporating intent propensities in personalized next best action recommendation. | Yuxi Zhang, Kexin Xie |
| 2019 | Sampling-bias-corrected neural modeling for large corpus item recommendations. | Xinyang Yi, Ji Yang, Lichan Hong, Derek Zhiyuan Cheng, Lukasz Heldt, Aditee Kumthekar, Zhe Zhao, Li Wei, Ed H. Chi |
| 2019 | An Advice Recommender System Based on Complaint Data Analysis. | Liang Yang, Daisuke Kitayama, Kazutoshi Sumiya |
| 2019 | A recommender system for heterogeneous and time sensitive environment. | Meng Wu, Ying Zhu, Qilian Yu, Bhargav Rajendra, Yunqi Zhao, Navid Aghdaie, Kazi A. Zaman |
| 2019 | Deep language-based critiquing for recommender systems. | Ga Wu, Kai Luo, Scott Sanner, Harold Soh |
| 2019 | Users in the loop: a psychologically-informed approach to similar item retrieval. | Amy A. Winecoff, Florin Brasoveanu, Bryce Casavant, Pearce Washabaugh, Matthew Graham |
| 2019 | Leveraging post-click feedback for content recommendations. | Hongyi Wen, Longqi Yang, Deborah Estrin |
| 2019 | Practical Lessons from Predicting New User Demographics for Ad Targeting. | Musen Wen, Zhen Xia, Deepak Kumar Vasthimal |
| 2019 | Optimal Delivery with Budget Constraint in E-Commerce Advertising. | Chao Wei, Weiru Zhang, Shengjie Sun, Fei Li, Xiaonan Meng, Yi Hu, Kuang-chih Lee, Hao Wang |
| 2019 | Predicting user routines with masked dilated convolutions. | Renzhong Wang, Dragomir Yankov, Michael R. Evans, Senthil Palanisamy, Siddhartha Arora, Wei Wu |