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ORCIDSarah Dean
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2020 – today
- 2024
[c23]Sarah Dean, Mihaela Curmei, Lillian J. Ratliff, Jamie Morgenstern, Maryam Fazel:
Emergent specialization from participation dynamics and multi-learner retraining. AISTATS 2024: 343-351- [c22]Eliot Shekhtman, Sarah Dean:
Strategic Usage in a Multi-Learner Setting. AISTATS 2024: 2665-2673 - [c21]Jinyan Su, Sarah Dean:
Learning from Streaming Data when Users Choose. ICML 2024 - [c20]Jerry Chee
, Shankar Kalyanaraman, Sindhu Kiranmai Ernala, Udi Weinsberg, Sarah Dean, Stratis Ioannidis:
Harm Mitigation in Recommender Systems under User Preference Dynamics. KDD 2024: 255-265 - [c19]Kimia Kazemian, Yahya Sattar, Sarah Dean:
Random features approximation for control-affine systems. L4DC 2024: 732-744 - [c18]Kianté Brantley, Zhichong Fang, Sarah Dean, Thorsten Joachims:
Ranking with Long-Term Constraints. WSDM 2024: 47-56 - [i33]Eliot Shekhtman, Sarah Dean:
Strategic Usage in a Multi-Learner Setting. CoRR abs/2401.16422 (2024) - [i32]Sarah Dean, Evan Dong, Meena Jagadeesan, Liu Leqi:
Accounting for AI and Users Shaping One Another: The Role of Mathematical Models. CoRR abs/2404.12366 (2024) - [i31]Rohan Banerjee, Rajat Kumar Jenamani, Sidharth Vasudev, Amal Nanavati, Sarah Dean, Tapomayukh Bhattacharjee:
To Ask or Not To Ask: Human-in-the-loop Contextual Bandits with Applications in Robot-Assisted Feeding. CoRR abs/2405.06908 (2024) - [i30]Jinyan Su, Sarah Dean:
Learning from Streaming Data when Users Choose. CoRR abs/2406.01481 (2024) - [i29]Kimia Kazemian, Yahya Sattar, Sarah Dean:
Random Features Approximation for Control-Affine Systems. CoRR abs/2406.06514 (2024) - [i28]Jerry Chee, Shankar Kalyanaraman, Sindhu Kiranmai Ernala, Udi Weinsberg, Sarah Dean, Stratis Ioannidis:
Harm Mitigation in Recommender Systems under User Preference Dynamics. CoRR abs/2406.09882 (2024) - [i27]Yahya Sattar, Yassir Jedra, Sarah Dean:
Learning Linear Dynamics from Bilinear Observations. CoRR abs/2409.16499 (2024) - 2023
- [c17]Thomas Krendl Gilbert, Nathan Lambert, Sarah Dean, Tom Zick, Aaron J. Snoswell, Soham Mehta:
Reward Reports for Reinforcement Learning. AIES 2023: 84-130 - [c16]Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus, Sarah Dean:
Modeling content creator incentives on algorithm-curated platforms. ICLR 2023 - [c15]Raunak Kumar, Sarah Dean, Robert Kleinberg:
Online Convex Optimization with Unbounded Memory. NeurIPS 2023 - [c14]Da Xu, Tobias Schnabel, Xiquan Cui, Sarah Dean, Aniket Anand Deshmukh, Bo Yang, Shipeng Yu:
Foreword for Workshop on Decision Making for Information Retrieval and Recommender Systems. WWW (Companion Volume) 2023: 920 - [i26]Ruqing Xu, Sarah Dean:
Decision-aid or Controller? Steering Human Decision Makers with Algorithms. CoRR abs/2303.13712 (2023) - [i25]Kianté Brantley, Zhichong Fang, Sarah Dean, Thorsten Joachims:
Ranking with Long-Term Constraints. CoRR abs/2307.04923 (2023) - [i24]Avinandan Bose, Mihaela Curmei, Daniel L. Jiang, Jamie Morgenstern, Sarah Dean, Lillian J. Ratliff, Maryam Fazel:
Initializing Services in Interactive ML Systems for Diverse Users. CoRR abs/2312.11846 (2023) - 2022
- [c13]Sarah Dean, Jamie Morgenstern:
Preference Dynamics Under Personalized Recommendations. EC 2022: 795-816 - [i23]Thomas Krendl Gilbert, Sarah Dean, Tom Zick, Nathan Lambert:
Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems. CoRR abs/2202.05716 (2022) - [i22]Thomas Krendl Gilbert, Sarah Dean, Nathan Lambert, Tom Zick, Aaron J. Snoswell:
Reward Reports for Reinforcement Learning. CoRR abs/2204.10817 (2022) - [i21]Sarah Dean, Jamie Morgenstern:
Preference Dynamics Under Personalized Recommendations. CoRR abs/2205.13026 (2022) - [i20]Sarah Dean, Mihaela Curmei, Lillian J. Ratliff, Jamie Morgenstern, Maryam Fazel:
Multi-learner risk reduction under endogenous participation dynamics. CoRR abs/2206.02667 (2022) - [i19]Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus, Sarah Dean:
Modeling Content Creator Incentives on Algorithm-Curated Platforms. CoRR abs/2206.13102 (2022) - [i18]Raunak Kumar, Sarah Dean, Robert D. Kleinberg:
Online Convex Optimization with Unbounded Memory. CoRR abs/2210.09903 (2022) - [i17]Liliaokeawawa Cothren, Gianluca Bianchin, Sarah Dean, Emiliano Dall'Anese:
Perception-Based Sampled-Data Optimization of Dynamical Systems. CoRR abs/2211.10020 (2022) - [i16]Fengyu Li, Sarah Dean:
Cross-Dataset Propensity Estimation for Debiasing Recommender Systems. CoRR abs/2212.13892 (2022) - 2021
- [b1]Sarah Dean:
Reliable Machine Learning in Feedback Systems. University of California, Berkeley, USA, 2021 - [c12]Andrew J. Taylor, Victor D. Dorobantu, Sarah Dean, Benjamin Recht, Yisong Yue, Aaron D. Ames:
Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty. CDC 2021: 6469-6476 - [c11]Mihaela Curmei, Sarah Dean, Benjamin Recht:
Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability. ICML 2021: 2265-2275 - [c10]Sarah Dean, Benjamin Recht:
Certainty Equivalent Perception-Based Control. L4DC 2021: 399-411 - [i15]McKane Andrus, Sarah Dean, Thomas Krendl Gilbert, Nathan Lambert, Tom Zick:
AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks. CoRR abs/2102.04255 (2021) - [i14]Sarah Dean, Thomas Krendl Gilbert, Nathan Lambert, Tom Zick:
Axes for Sociotechnical Inquiry in AI Research. CoRR abs/2105.06551 (2021) - [i13]Mihaela Curmei, Sarah Dean, Benjamin Recht:
Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability. CoRR abs/2107.00833 (2021) - 2020
- [j1]Sarah Dean, Horia Mania, Nikolai Matni, Benjamin Recht, Stephen Tu:
On the Sample Complexity of the Linear Quadratic Regulator. Found. Comput. Math. 20(4): 633-679 (2020) - [c9]Sarah Dean, Andrew J. Taylor, Ryan K. Cosner, Benjamin Recht, Aaron D. Ames:
Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions. CoRL 2020: 654-670 - [c8]Sarah Dean, Sarah Rich, Benjamin Recht:
Recommendations and user agency: the reachability of collaboratively-filtered information. FAT* 2020: 436-445 - [c7]Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Björkegren, Moritz Hardt, Joshua Blumenstock:
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning. ICML 2020: 8158-8168 - [c6]McKane Andrus, Sarah Dean, Thomas Krendl Gilbert, Nathan Lambert, Tom Zick:
AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks. ISTAS 2020: 72-79 - [c5]Sarah Dean, Nikolai Matni, Benjamin Recht, Vickie Ye:
Robust Guarantees for Perception-Based Control. L4DC 2020: 350-360 - [i12]Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Björkegren, Moritz Hardt, Joshua Blumenstock:
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning. CoRR abs/2003.06740 (2020) - [i11]Sarah Dean, Benjamin Recht:
Certainty Equivalent Perception-Based Control. CoRR abs/2008.12332 (2020) - [i10]Sarah Dean, Andrew J. Taylor, Ryan K. Cosner, Benjamin Recht, Aaron D. Ames:
Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions. CoRR abs/2010.16001 (2020) - [i9]Karl Krauth, Sarah Dean, Alex Zhao, Wenshuo Guo, Mihaela Curmei, Benjamin Recht, Michael I. Jordan:
Do Offline Metrics Predict Online Performance in Recommender Systems? CoRR abs/2011.07931 (2020) - [i8]Andrew J. Taylor, Victor D. Dorobantu, Sarah Dean, Benjamin Recht, Yisong Yue, Aaron D. Ames:
Towards Robust Data-Driven Control Synthesis for Nonlinear Systems with Actuation Uncertainty. CoRR abs/2011.10730 (2020)
2010 – 2019
- 2019
- [c4]Sarah Dean, Stephen Tu, Nikolai Matni, Benjamin Recht:
Safely Learning to Control the Constrained Linear Quadratic Regulator. ACC 2019: 5582-5588 - [c3]Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt:
Delayed Impact of Fair Machine Learning. IJCAI 2019: 6196-6200 - [i7]Sarah Dean, Nikolai Matni, Benjamin Recht, Vickie Ye:
Robust Guarantees for Perception-Based Control. CoRR abs/1907.03680 (2019) - [i6]Sarah Dean, Sarah Rich, Benjamin Recht:
Recommendations and User Agency: The Reachability of Collaboratively-Filtered Information. CoRR abs/1912.10068 (2019) - 2018
- [c2]Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt:
Delayed Impact of Fair Machine Learning. ICML 2018: 3156-3164 - [c1]Sarah Dean, Horia Mania, Nikolai Matni, Benjamin Recht, Stephen Tu:
Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator. NeurIPS 2018: 4192-4201 - [i5]Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt:
Delayed Impact of Fair Machine Learning. CoRR abs/1803.04383 (2018) - [i4]Sarah Dean, Horia Mania, Nikolai Matni, Benjamin Recht, Stephen Tu:
Regret Bounds for Robust Adaptive Control of the Linear Quadratic Regulator. CoRR abs/1805.09388 (2018) - [i3]Roel Dobbe, Sarah Dean, Thomas Krendl Gilbert, Nitin Kohli:
A Broader View on Bias in Automated Decision-Making: Reflecting on Epistemology and Dynamics. CoRR abs/1807.00553 (2018) - [i2]Sarah Dean, Stephen Tu, Nikolai Matni, Benjamin Recht:
Safely Learning to Control the Constrained Linear Quadratic Regulator. CoRR abs/1809.10121 (2018) - 2017
- [i1]Sarah Dean, Horia Mania, Nikolai Matni, Benjamin Recht, Stephen Tu:
On the Sample Complexity of the Linear Quadratic Regulator. CoRR abs/1710.01688 (2017)
Coauthor Index
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last updated on 2024-10-17 20:29 CEST by the dblp team
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