1. R. Jia, R. Dong, P. Ganesh, S. S. Sastry, C. Spanos. Towards a Theory of Free-Lunch Privacy in Cyber-Physical Systems. In the 55th Annual Allerton Conference on Communication, Control, and Computing, 2017.
2. T. Westenbroek, R. Dong, L. J. Ratliff, S. S. Sastry. Statistical Estimation in Competitive Settings with Strategic Data Sources. In the IEEE 56th Conference on Decision and Control (CDC), 2017.
3. R. Jia, R. Dong, S. S. Sastry, C. Spanos. Optimal Sensor-Controller Codesign for Privacy in Dynamical Systems. In the IEEE 56th Conference on Decision and Control (CDC), 2017.
4. D. Calderone, R. Dong, S. S. Sastry. External-Cost Wardrop Equilibria in Routing Games. In the IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), 2017.
5. R. Jia, R. Dong, S. S. Sastry, C. J. Spanos. Privacy-Enhanced Architecture for Occupancy-based HVAC Control. In the 8th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), 2017.
6. Dorsa Sadigh, Anca D. Dragan, S. Shankar Sastry, Sanjit A. Seshia. Active Preference-Based Learning of Reward Functions. Proceedings of Robotics: Science and Systems (RSS), July 2017. [PDF]
Negar Mehr, Dorsa Sadigh, Roberto Horowitz, S. Shankar Sastry, Sanjit A. Seshia. Stochastic Predictive Freeway Ramp Metering from Signal Temporal Logic Specifications. Proceedings of the American Control Conference, May 2017. [PDF]
Eric Mazumdar, Roy Dong, Vicenc Rubies Royo, Claire Tomlin, S. Shankar Sastry. A Multi-Armed Bandit Approach for Online Expert Selection in Markov Decision Processes. arXiv:1707.05714v1 [cs.SY] 18 Jul 2017. [PDF]
9. Ioannis Konstantakopoulos, Lillian J. Ratliff, Ming Jin, S. Shankar Sastry, and Costas Spanos. A Robust Utility Learning Framework via Inverse Optimization. IEEE Transactions on Control Systems Technology, PP(99):1--17, 2017.
10. Kamil Nar, Lillian J. Ratliff, and S. Shankar Sastry. Learning Prospect Theory Value Function and Reference Point of a Sequential Decision Maker. In Proceedings of the 56th IEEE Confefence on Decision and Control, 2017.
11. Eric Mazumdar, Lillian J. Ratliff, Tanner Fiez, and S. Shankar Sastry. Gradient--Based Inverse Risk-Sensitive Reinforcement Learning with Applications. In Proceedings of the 56th IEEE Confefence on Decision and Control, 2017.
12. Jaime F. Fisac, Monica A. Gates, Jessica B. Hamrick, Chang Liu, Dylan Hadfield-Menell, Malayandi Palaniappan, Dhruv Malik, S. Shankar Sastry, Thomas L. Griffiths, and Anca D. Dragan. Pragmatic-Pedagogic Value Alignment. ISRR 2017. [PDF]