| 2025 | EMNLP | MATCH: Task-Driven Code Evaluation through Contrastive Learning. | Marah Ghoummaid, Vladimir Tchuiev, Ofek Glick, Michal Moshkovitz, Dotan Di Castro |
| 2024 | AAAI | Principal-Agent Reward Shaping in MDPs. | Omer Ben-Porat, Yishay Mansour, Michal Moshkovitz, Boaz Taitler |
| 2024 | ALT | Partially Interpretable Models with Guarantees on Coverage and Accuracy. | Nave Frost, Zachary C. Lipton, Yishay Mansour, Michal Moshkovitz |
| 2023 | ALT | Online k-means Clustering on Arbitrary Data Streams. | Robi Bhattacharjee, Jacob Imola, Michal Moshkovitz, Sanjoy Dasgupta |
| 2022 | ICML | Framework for Evaluating Faithfulness of Local Explanations. | Sanjoy Dasgupta, Nave Frost, Michal Moshkovitz |
| 2021 | ALT | No-substitution k-means Clustering with Adversarial Order. | Robi Bhattacharjee, Michal Moshkovitz |
| 2021 | ALT | Unexpected Effects of Online no-Substitution k-means Clustering. | Michal Moshkovitz |
| 2021 | COLT | Bounded Memory Active Learning through Enriched Queries. | Max Hopkins, Daniel Kane, Shachar Lovett, Michal Moshkovitz |
| 2021 | ICML | Connecting Interpretability and Robustness in Decision Trees through Separation. | Michal Moshkovitz, Yao-Yuan Yang, Kamalika Chaudhuri |
| 2020 | ICML | Explainable k-Means and k-Medians Clustering. | Michal Moshkovitz, Sanjoy Dasgupta, Cyrus Rashtchian, Nave Frost |
| 2017 | COLT | Mixing Implies Lower Bounds for Space Bounded Learning. | Dana Moshkovitz, Michal Moshkovitz |
| 2014 | ISIT | Control your information for better predictions. | Michal Moshkovitz, Naftali Tishby |