Stephen Tu
Stephen Tu
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Cited by
Cited by
Machine learning classification over encrypted data
R Bost, RA Popa, S Tu, S Goldwasser
Cryptology ePrint Archive, 2014
On the sample complexity of the linear quadratic regulator
S Dean, H Mania, N Matni, B Recht, S Tu
Foundations of Computational Mathematics 20 (4), 633-679, 2020
Speedy transactions in multicore in-memory databases
S Tu, W Zheng, E Kohler, B Liskov, S Madden
Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems …, 2013
Processing analytical queries over encrypted data
SL Tu, MF Kaashoek, SR Madden, N Zeldovich
Association for Computing Machinery (ACM), 2013
Low-rank solutions of linear matrix equations via procrustes flow
S Tu, R Boczar, M Simchowitz, M Soltanolkotabi, B Recht
arXiv preprint arXiv:1507.03566, 2015
Learning without mixing: Towards a sharp analysis of linear system identification
M Simchowitz, H Mania, S Tu, MI Jordan, B Recht
Conference On Learning Theory, 439-473, 2018
Regret bounds for robust adaptive control of the linear quadratic regulator
S Dean, H Mania, N Matni, B Recht, S Tu
Advances in Neural Information Processing Systems 31, 2018
Certainty equivalence is efficient for linear quadratic control
H Mania, S Tu, B Recht
Advances in Neural Information Processing Systems 32, 2019
Learning control barrier functions from expert demonstrations
A Robey, H Hu, L Lindemann, H Zhang, DV Dimarogonas, S Tu, N Matni
2020 59th IEEE Conference on Decision and Control (CDC), 3717-3724, 2020
The gap between model-based and model-free methods on the linear quadratic regulator: An asymptotic viewpoint
S Tu, B Recht
Conference on Learning Theory, 3036-3083, 2019
Anti-caching: A new approach to database management system architecture
J DeBrabant, A Pavlo, S Tu, M Stonebraker, S Zdonik
Proceedings of the VLDB Endowment 6 (14), 1942-1953, 2013
Fast databases with fast durability and recovery through multicore parallelism
W Zheng, S Tu, E Kohler, B Liskov
11th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2014
Safely learning to control the constrained linear quadratic regulator
S Dean, S Tu, N Matni, B Recht
2019 American Control Conference (ACC), 5582-5588, 2019
Least-squares temporal difference learning for the linear quadratic regulator
S Tu, B Recht
International Conference on Machine Learning, 5005-5014, 2018
Observational overfitting in reinforcement learning
X Song, Y Jiang, S Tu, Y Du, B Neyshabur
arXiv preprint arXiv:1912.02975, 2019
Robots that ask for help: Uncertainty alignment for large language model planners
AZ Ren, A Dixit, A Bodrova, S Singh, S Tu, N Brown, P Xu, L Takayama, ...
arXiv preprint arXiv:2307.01928, 2023
From self-tuning regulators to reinforcement learning and back again
N Matni, A Proutiere, A Rantzer, S Tu
2019 IEEE 58th Conference on Decision and Control (CDC), 3724-3740, 2019
Learning stability certificates from data
N Boffi, S Tu, N Matni, JJ Slotine, V Sindhwani
Conference on Robot Learning, 1341-1350, 2021
Certainty equivalent control of LQR is efficient
H Mania, S Tu, B Recht
arXiv preprint arXiv:1902.07826, 2019
Non-asymptotic analysis of robust control from coarse-grained identification
S Tu, R Boczar, A Packard, B Recht
arXiv preprint arXiv:1707.04791, 2017
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