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Dive into the research topics where Anirudha Majumdar is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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MEMS Airflow Sensors for Model-Based UAV Control in Extreme Wind Conditions
Air Force Office of Scientific Research
10/15/21 → 10/14/24
Project: Research project
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Learning Control Policies for Robots with Guaranteed Out-of-Distribution Generalization
9/1/21 → 8/31/24
Project: Research project
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NSF CAREER: Generalization and Safety Guarantees for Learning-Based Control of Robots
NSF - National Science Foundation
8/1/21 → 7/31/26
Project: Research project
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Structured Deep Learning for Modeling and Controlling High-Dimensional Dynamical Systems
9/24/18 → 9/23/22
Project: Research project
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CRII: RI: Memory-efficient Representations for Robot Tasks: Lower Bounds and Scalable Algorithms
NSF - National Science Foundation
9/1/18 → 8/31/20
Project: Research project
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Distributionally Robust Policy Learning via Adversarial Environment Generation
Ren, A. Z. & Majumdar, A., Apr 1 2022, In: IEEE Robotics and Automation Letters. 7, 2, p. 1379-1386 8 p.Research output: Contribution to journal › Article › peer-review
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Robust Control Under Uncertainty via Bounded Rationality and Differential Privacy
Pacelli, V. & Majumdar, A., 2022, 2022 IEEE International Conference on Robotics and Automation, ICRA 2022. Institute of Electrical and Electronics Engineers Inc., p. 3467-3474 8 p. (Proceedings - IEEE International Conference on Robotics and Automation).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Stronger Generalization Guarantees for Robot Learning by Combining Generative Models and Real-World Data
Agarwal, A., Veer, S., Ren, A. Z. & Majumdar, A., 2022, 2022 IEEE International Conference on Robotics and Automation, ICRA 2022. Institute of Electrical and Electronics Engineers Inc., p. 4414-4421 8 p. (Proceedings - IEEE International Conference on Robotics and Automation).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability
Farid, A. & Majumdar, A., 2021, Advances in Neural Information Processing Systems 34 - 35th Conference on Neural Information Processing Systems, NeurIPS 2021. Ranzato, MA., Beygelzimer, A., Dauphin, Y., Liang, P. S. & Wortman Vaughan, J. (eds.). Neural information processing systems foundation, p. 2173-2186 14 p. (Advances in Neural Information Processing Systems; vol. 3).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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How Should a Robot Assess Risk? Towards an Axiomatic Theory of Risk in Robotics
Majumdar, A. & Pavone, M., 2020, Springer Proceedings in Advanced Robotics. Springer Science and Business Media B.V., p. 75-84 10 p. (Springer Proceedings in Advanced Robotics; vol. 10).Research output: Chapter in Book/Report/Conference proceeding › Chapter
45 Scopus citations