| 2025 | ICLR | Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness. | Maayan Ehrenberg, Roy Ganz, Nir Rosenfeld |
| 2025 | ICML | A Market for Accuracy: Classification Under Competition. | Ohad Einav, Nir Rosenfeld |
| 2025 | ICML | Learning Classifiers That Induce Markets. | Yonatan Sommer, Ivri Hikri, Lotan Amit, Nir Rosenfeld |
| 2024 | ICLR | Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces. | Omer Nahum, Gali Noti, David C. Parkes, Nir Rosenfeld |
| 2024 | ICML | Classification Under Strategic Self-Selection. | Guy Horowitz, Yonatan Sommer, Moran Koren, Nir Rosenfeld |
| 2024 | ICML | One-Shot Strategic Classification Under Unknown Costs. | Elan Rosenfeld, Nir Rosenfeld |
| 2024 | WSDM | Strategic ML: How to Learn With Data That 'Behaves'. | Nir Rosenfeld |
| 2023 | ICLR | Strategic Classification with Graph Neural Networks. | Itay Eilat, Ben Finkelshtein, Chaim Baskin, Nir Rosenfeld |
| 2023 | ICML | Performative Recommendation: Diversifying Content via Strategic Incentives. | Itay Eilat, Nir Rosenfeld |
| 2023 | ICML | Causal Strategic Classification: A Tale of Two Shifts. | Guy Horowitz, Nir Rosenfeld |
| 2023 | ICML | Learning to Suggest Breaks: Sustainable Optimization of Long-Term User Engagement. | Eden Saig, Nir Rosenfeld |
| 2022 | ICML | Generalized Strategic Classification and the Case of Aligned Incentives. | Sagi Levanon, Nir Rosenfeld |
| 2022 | ICML | Strategic Representation. | Vineet Nair, Ganesh Ghalme, Inbal Talgam-Cohen, Nir Rosenfeld |
| 2021 | ICML | Strategic Classification in the Dark. | Ganesh Ghalme, Vineet Nair, Itay Eilat, Inbal Talgam-Cohen, Nir Rosenfeld |
| 2021 | ICML | Learning Representations by Humans, for Humans. | Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, David C. Parkes |
| 2021 | ICML | Strategic Classification Made Practical. | Sagi Levanon, Nir Rosenfeld |
| 2020 | ICML | Predicting Choice with Set-Dependent Aggregation. | Nir Rosenfeld, Kojin Oshiba, Yaron Singer |
| 2020 | WWW | A Kernel of Truth: Determining Rumor Veracity on Twitter by Diffusion Pattern Alone. | Nir Rosenfeld, Aron Szanto, David C. Parkes |
| 2018 | AISTATS | Semi-Supervised Learning with Competitive Infection Models. | Nir Rosenfeld, Amir Globerson |
| 2018 | AISTATS | Discriminative Learning of Prediction Intervals. | Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov |
| 2018 | ICML | Learning to Optimize Combinatorial Functions. | Nir Rosenfeld, Eric Balkanski, Amir Globerson, Yaron Singer |
| 2017 | WWW | Predicting Counterfactuals from Large Historical Data and Small Randomized Trials. | Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov |
| 2016 | WSDM | Discriminative Learning of Infection Models. | Nir Rosenfeld, Mor Nitzan, Amir Globerson |
| 2014 | AISTATS | Learning Structured Models with the AUC Loss and Its Generalizations. | Nir Rosenfeld, Ofer Meshi, Daniel Tarlow, Amir Globerson |