2020 Publications



1. Afolabi, Oladapo and Yang, Allen and Sastry, Shankar S, DeepSDF x Sim (3): Extending DeepSDF for automatic 3D shape retrieval and similarity transform estimation, arXiv preprint arXiv:2004.09048, 2020. [PDF]

2. Dexter R.R. Scobee and S. Shankar Sastry, Maximum Likelihood Constraint Inference for Inverse Reinforcement Learning, International Conference on Learning Representations (ICLR), 2020. [PDF]

3. Andreea Bobu, Dexter R.R. Scobee, Jaime F. Fisac, S. Shankar Sastry, and Anca D. Dragan, LESS is More: Rethinking Probabilistic Models of Human Behavior, ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2020. [PDF]

4. Eric Mazumdar, Lillian J. Ratliff, Micheal I. Jordan, S. Shankar Sastry. Policy-Gradient Algorithms Have No Guarantees of Convergence in Linear Quadratic Games. AAMAS, 2020. [PDF]

5. Valmik Prabhu, Amay Saxena, and S. Shankar Sastry. Exponentially Stable First Order Control on Matrix Lie Groups. arXiv preprint arXiv:2004.00239, 2020. [PDF]

6. Tyler Westenbroek, Fernando Castaņeda, Ayush Agrawal, S. Shankar Sastry, Koushil Sreenath. Learning Min-norm Stabilizing Control Laws forSystems with Unknown Dynamics. Arxiv 2004.10331(2020). [PDF]

7. Tyler Westenbroek, Eric Mazumdar, David Fridovich-Keil, Valmik Prabhu, Claire J. Tomlin and S. Shankar Sastry. Technichal Report: Adaptive Control for Linearizable Systems using On-Policy Reinforcement Learning. arxiv2004.02766, 2020. [PDF]

8. K. Nar and S. S. Sastry. Richness of training data does not suffice: Robustness of neural networks requires richness of hidden-layer activations. Workshop on Uncertainty and Robustness in Deep Learning, International Conference on Machine Learning, 2020. [PDF]

9. P Dayani, N Orr, A Thomopoulos, V Saran, S Krishnaswamy, E Zhang, N Hu, D McPherson, J Menke, A Yang, K Vetter (2020). Immersive Operation of a Semi-Autonomous Aerial Platform for Detecting and Mapping Radiation. In 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) (pp. 1-3). IEEE. [PDF]

10. Tyler Westenbroek, Roy Dong, Lillian J. Ratliff, S. Shankar Sastry. Competitive Statistical Estimation with Strategic Data Sources. IEEE Transactions on Automatic Control. [PDF]

11. Tyler Westenbroek;David Fridovich-Keil;Eric Mazumdar;Shreyas Arora;Valmik Prabhu;S. Shankar Sastry;Claire J. Tomlin. Feedback Linearization for Uncertain Systems via Reinforcement Learning. 2020 IEEE International Conference on Robotics and Automation (ICRA). [PDF]

12. Vicenį Rubies-Royo;Eric Mazumdar;Roy Dong;Claire Tomlin;S. Shankar Sastry. Expert Selection in High-Dimensional Markov Decision Processes. 2020 59th IEEE Conference on Decision and Control (CDC). [PDF]

13. Kshama Dwarakanath, S Shankar Sastry. Learning to play collaborative-competitive games. [PDF]

14. Eric Mazumdar, Tyler Westenbroek, Michael I Jordan, S Shankar Sastry. High Confidence Sets for Trajectories of Stochastic Time-Varying Nonlinear Systems. 2020 59th IEEE Conference on Decision and Control (CDC) (Pages 4275-4280). [PDF]

15. Fernando Castaņeda, Mathias Wulfman, Ayush Agrawal, Tyler Westenbroek, Shankar Sastry, Claire Tomlin, Koushil Sreenath. Improving input-output linearizing controllers for bipedal robots via reinforcement learning. Learning for Dynamics and Control (Pages 990-999). [PDF]

16. Eric Mazumdar, Lillian J Ratliff, S Shankar Sastry. On gradient-based learning in continuous games. SIAM Journal on Mathematics of Data Science (Volume 2, Issue 1, Pages 103-131).

17. Jaime F Fisac, Chang Liu, Jessica B Hamrick, Shankar Sastry, J Karl Hedrick, Thomas L Griffiths, Anca D Dragan. Generating plans that predict themselves. Algorithmic Foundations of Robotics XII (Pages 144-159). [PDF]