Anirudha Majumdar

Source: Scopus
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1 Finished
1 Active

Structured Deep Learning for Modeling and Controlling High-Dimensional Dynamical Systems
Majumdar, A.
Office of Naval Research - MA
9/24/18 → 9/23/22
Project: Research project
CRII: RI: Memory-efficient Representations for Robot Tasks: Lower Bounds and Scalable Algorithms
Majumdar, A.
NSF - National Science Foundation
9/1/18 → 8/31/20
Project: Research project

425 Citations
10 h-Index
8 Conference contribution
7 Article
2 Conference article
1 Paper

PAC-Bayes control: learning policies that provably generalize to novel environments
Majumdar, A., Farid, A. & Sonar, A., 2020, (Accepted/In press) In: International Journal of Robotics Research.
Research output: Contribution to journal › Article › peer-review
A Framework for Time-Consistent, Risk-Sensitive Model Predictive Control: Theory and Algorithms
Singh, S., Chow, Y., Majumdar, A. & Pavone, M., Jul 2019, In: IEEE Transactions on Automatic Control. 64, 7, p. 2905-2912 8 p., 8485726.
Research output: Contribution to journal › Article › peer-review
3 Scopus citations
DSOS and SDSOS optimization: More tractable alternatives to sum of squares and semidefinite optimization
Ahmadi, A. A. & Majumdar, A., 2019, In: SIAM Journal on Applied Algebra and Geometry. 3, 2, p. 193-230 38 p.
Research output: Contribution to journal › Article › peer-review
29 Scopus citations
Task-Driven Estimation and Control via Information Bottlenecks
Pacelli, V. & Majumdar, A., May 2019, 2019 International Conference on Robotics and Automation, ICRA 2019. Institute of Electrical and Electronics Engineers Inc., p. 2061-2067 7 p. 8794213. (Proceedings - IEEE International Conference on Robotics and Automation; vol. 2019-May).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Risk-sensitive inverse reinforcement learning via semi- and non-parametric methods
Singh, S., Lacotte, J., Majumdar, A. & Pavone, M., Dec 1 2018, In: International Journal of Robotics Research. 37, 13-14, p. 1713-1740 28 p.
Research output: Contribution to journal › Article › peer-review
3 Scopus citations

Structured Deep Learning for Modeling and Controlling High-Dimensional Dynamical Systems

CRII: RI: Memory-efficient Representations for Robot Tasks: Lower Bounds and Scalable Algorithms

PAC-Bayes control: learning policies that provably generalize to novel environments

A Framework for Time-Consistent, Risk-Sensitive Model Predictive Control: Theory and Algorithms

DSOS and SDSOS optimization: More tractable alternatives to sum of squares and semidefinite optimization

Task-Driven Estimation and Control via Information Bottlenecks

Risk-sensitive inverse reinforcement learning via semi- and non-parametric methods