| 2022 | HCOMP | When More Data Lead Us Astray: Active Data Acquisition in the Presence of Label Bias. | Yunyi Li, Maria De-Arteaga, Maytal Saar-Tsechansky |
| 2021 | IJCAI | Human-AI Collaboration with Bandit Feedback. | Ruijiang Gao, Maytal Saar-Tsechansky, Maria De-Arteaga, Ligong Han, Min Kyung Lee, Matthew Lease |
| 2020 | AAAI | Cost-Accuracy Aware Adaptive Labeling for Active Learning. | Ruijiang Gao, Maytal Saar-Tsechansky |
| 2018 | ICIS | The Role of Personality in the Diffusion of Digital Media. | Haris Krijestorac, Rajiv Garg, Maytal Saar-Tsechansky |
| 2017 | AAAI | Designing Better Playlists with Monte Carlo Tree Search. | Elad Liebman, Piyush Khandelwal, Maytal Saar-Tsechansky, Peter Stone |
| 2016 | ICIS | Using Retweets to Shape our Online Persona: a Topic Modeling Approach. | Hilah Geva, Gal Oestreicher-Singer, Maytal Saar-Tsechansky |
| 2016 | ICIS | Who's A Good Decision Maker? Data-Driven Expert Worker Ranking under Unobservable Quality. | Tomer Geva, Maytal Saar-Tsechansky |
| 2004 | ICDM | Active Feature-Value Acquisition for Classifier Induction. | Prem Melville, Maytal Saar-Tsechansky, Foster J. Provost, Raymond J. Mooney |
| 2001 | IJCAI | Active Learning for Class Probability Estimation and Ranking. | Maytal Saar-Tsechansky, Foster J. Provost |