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Anand Siththaranjan
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2020 – today
- 2024
- [c4]Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell:
Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF. ICLR 2024 - [c3]Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, Anca D. Dragan:
AI Alignment with Changing and Influenceable Reward Functions. ICML 2024 - [i6]Jingqi Li, Anand Siththaranjan, Somayeh Sojoudi, Claire J. Tomlin, Andrea Bajcsy:
Intent Demonstration in General-Sum Dynamic Games via Iterative Linear-Quadratic Approximations. CoRR abs/2402.10182 (2024) - [i5]Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, Anca D. Dragan:
AI Alignment with Changing and Influenceable Reward Functions. CoRR abs/2405.17713 (2024) - 2023
- [j1]Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell:
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. Trans. Mach. Learn. Res. 2023 (2023) - [i4]Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell:
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. CoRR abs/2307.15217 (2023) - [i3]Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell:
Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF. CoRR abs/2312.08358 (2023) - 2022
- [c2]Tyler Westenbroek, Anand Siththaranjan, Mohsin Sarwari, Claire J. Tomlin, S. Shankar Sastry:
On the Computational Consequences of Cost Function Design in Nonlinear Optimal Control. CDC 2022: 7423-7430 - [i2]Tyler Westenbroek, Anand Siththaranjan, Mohsin Sarwari, Claire J. Tomlin, Shankar S. Sastry:
On the Computational Consequences of Cost Function Design in Nonlinear Optimal Control. CoRR abs/2204.01986 (2022) - 2021
- [c1]Andrea Bajcsy, Anand Siththaranjan, Claire J. Tomlin, Anca D. Dragan:
Analyzing Human Models that Adapt Online. ICRA 2021: 2754-2760 - [i1]Andrea Bajcsy, Anand Siththaranjan, Claire J. Tomlin, Anca D. Dragan:
Analyzing Human Models that Adapt Online. CoRR abs/2103.05746 (2021)
Coauthor Index
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