Sarah Dean

According to our database, Sarah Dean authored at least 29 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Strategic Usage in a Multi-Learner Setting.

Eliot Shekhtman, Sarah Dean

CoRR, 2024

Ranking with Long-Term Constraints.

Kianté Brantley, Zhichong Fang, Sarah Dean, Thorsten Joachims

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

2023

Initializing Services in Interactive ML Systems for Diverse Users.

Avinandan Bose, Mihaela Curmei, Daniel L. Jiang, Jamie Morgenstern, Sarah Dean, Lillian J. Ratliff, Maryam Fazel

CoRR, 2023

Decision-aid or Controller? Steering Human Decision Makers with Algorithms.

Ruqing Xu, Sarah Dean

CoRR, 2023

Foreword for Workshop on Decision Making for Information Retrieval and Recommender Systems.

Da Xu, Tobias Schnabel, Xiquan Cui, Sarah Dean, Aniket Anand Deshmukh, Bo Yang, Shipeng Yu

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Online Convex Optimization with Unbounded Memory.

Raunak Kumar, Sarah Dean, Robert Kleinberg

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Modeling content creator incentives on algorithm-curated platforms.

Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus, Sarah Dean

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Reward Reports for Reinforcement Learning.

Thomas Krendl Gilbert, Nathan Lambert, Sarah Dean, Tom Zick, Aaron J. Snoswell, Soham Mehta

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022

Cross-Dataset Propensity Estimation for Debiasing Recommender Systems.

Fengyu Li, Sarah Dean

CoRR, 2022

Perception-Based Sampled-Data Optimization of Dynamical Systems.

Liliaokeawawa Cothren, Gianluca Bianchin, Sarah Dean, Emiliano Dall'Anese

CoRR, 2022

Multi-learner risk reduction under endogenous participation dynamics.

Sarah Dean, Mihaela Curmei, Lillian J. Ratliff, Jamie Morgenstern, Maryam Fazel

CoRR, 2022

Reward Reports for Reinforcement Learning.

Thomas Krendl Gilbert, Sarah Dean, Nathan Lambert, Tom Zick, Aaron J. Snoswell

CoRR, 2022

Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems.

Thomas Krendl Gilbert, Sarah Dean, Tom Zick, Nathan Lambert

CoRR, 2022

Preference Dynamics Under Personalized Recommendations.

Sarah Dean, Jamie Morgenstern

Proceedings of the EC '22: The 23rd ACM Conference on Economics and Computation, Boulder, CO, USA, July 11, 2022

2021

Axes for Sociotechnical Inquiry in AI Research.

Sarah Dean, Thomas Krendl Gilbert, Nathan Lambert, Tom Zick

CoRR, 2021

Certainty Equivalent Perception-Based Control.

Sarah Dean, Benjamin Recht

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability.

Mihaela Curmei, Sarah Dean, Benjamin Recht

Proceedings of the 38th International Conference on Machine Learning, 2021

Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty.

Andrew J. Taylor, Victor D. Dorobantu, Sarah Dean, Benjamin Recht, Yisong Yue, Aaron D. Ames

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

On the Sample Complexity of the Linear Quadratic Regulator.

Sarah Dean, Horia Mania, Nikolai Matni, Benjamin Recht, Stephen Tu

Found. Comput. Math., 2020

Do Offline Metrics Predict Online Performance in Recommender Systems?

Karl Krauth, Sarah Dean, Alex Zhao, Wenshuo Guo, Mihaela Curmei, Benjamin Recht, Michael I. Jordan

CoRR, 2020

Robust Guarantees for Perception-Based Control.

Sarah Dean, Nikolai Matni, Benjamin Recht, Vickie Ye

Proceedings of the 2nd Annual Conference on Learning for Dynamics and Control, 2020

AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks.

McKane Andrus, Sarah Dean, Thomas Krendl Gilbert, Nathan Lambert, Tom Zick

Proceedings of the IEEE International Symposium on Technology and Society, 2020

Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning.

Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Björkegren, Moritz Hardt, Joshua Blumenstock

Proceedings of the 37th International Conference on Machine Learning, 2020

Recommendations and user agency: the reachability of collaboratively-filtered information.

Sarah Dean, Sarah Rich, Benjamin Recht

Proceedings of the FAT* '20: Conference on Fairness, 2020

Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions.

Sarah Dean, Andrew J. Taylor, Ryan K. Cosner, Benjamin Recht, Aaron D. Ames

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Safely Learning to Control the Constrained Linear Quadratic Regulator.

Sarah Dean, Stephen Tu, Nikolai Matni, Benjamin Recht

Proceedings of the 2019 American Control Conference, 2019

2018

A Broader View on Bias in Automated Decision-Making: Reflecting on Epistemology and Dynamics.

Roel Dobbe, Sarah Dean, Thomas Krendl Gilbert, Nitin Kohli

CoRR, 2018

Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator.

Sarah Dean, Horia Mania, Nikolai Matni, Benjamin Recht, Stephen Tu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Delayed Impact of Fair Machine Learning.

Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt

Proceedings of the 35th International Conference on Machine Learning, 2018