| 2026 | AAAI | Moral Change or Noise? On Problems of Aligning AI with Temporally Unstable Human Feedback. | Vijay Keswani, Cyrus Cousins, Breanna K. Nguyen, Vincent Conitzer, Hoda Heidari, Jana Schaich Borg, Walter Sinnott-Armstrong |
| 2024 | AISTATS | To Pool or Not To Pool: Analyzing the Regularizing Effects of Group-Fair Training on Shared Models. | Cyrus Cousins, I. Elizabeth Kumar, Suresh Venkatasubramanian |
| 2023 | AISTATS | Revisiting Fair-PAC Learning and the Axioms of Cardinal Welfare. | Cyrus Cousins |
| 2023 | SAGT | Into the Unknown: Assigning Reviewers to Papers with Uncertain Affinities. | Cyrus Cousins, Justin Payan, Yair Zick |
| 2021 | ICML | Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees. | Alessio Mazzetto, Cyrus Cousins, Dylan Sam, Stephen H. Bach, Eli Upfal |
| 2021 | KDD | Bavarian: Betweenness Centrality Approximation with Variance-Aware Rademacher Averages. | Cyrus Cousins, Chloe Wohlgemuth, Matteo Riondato |
| 2020 | KDD | MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. | Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato |
| 2019 | UAI | Empirical Mechanism Design: Designing Mechanisms from Data. | Enrique Areyan Viqueira, Cyrus Cousins, Yasser Mohammad, Amy Greenwald |
| 2018 | SIGMOD | Towards Interactive Curation & Automatic Tuning of ML Pipelines. | Carsten Binnig, Benedetto Buratti, Yeounoh Chung, Cyrus Cousins, Tim Kraska, Zeyuan Shang, Eli Upfal, Robert C. Zeleznik, Emanuel Zgraggen |
| 2017 | DSAA | The k-Nearest Representatives Classifier: A Distance-Based Classifier with Strong Generalization Bounds. | Cyrus Cousins, Eli Upfal |