Jacob Steinhardt
Jacob Steinhardt
Verified email at cs.stanford.edu - Homepage
Cited by
Cited by
Concrete problems in AI safety
D Amodei, C Olah, J Steinhardt, P Christiano, J Schulman, D Mané
arXiv preprint arXiv:1606.06565, 2016
Certified defenses against adversarial examples
A Raghunathan, J Steinhardt, P Liang
arXiv preprint arXiv:1801.09344, 2018
The malicious use of artificial intelligence: Forecasting, prevention, and mitigation
M Brundage, S Avin, J Clark, H Toner, P Eckersley, B Garfinkel, A Dafoe, ...
arXiv preprint arXiv:1802.07228, 2018
Certified defenses for data poisoning attacks
J Steinhardt, PW Koh, P Liang
Proceedings of the 31st International Conference on Neural Information …, 2017
Semidefinite relaxations for certifying robustness to adversarial examples
A Raghunathan, J Steinhardt, P Liang
arXiv preprint arXiv:1811.01057, 2018
Learning from untrusted data
M Charikar, J Steinhardt, G Valiant
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017
Natural adversarial examples
D Hendrycks, K Zhao, S Basart, J Steinhardt, D Song
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
Troubling trends in machine learning scholarship
ZC Lipton, J Steinhardt
arXiv preprint arXiv:1807.03341, 2018
Sever: A robust meta-algorithm for stochastic optimization
I Diakonikolas, G Kamath, D Kane, J Li, J Steinhardt, A Stewart
International Conference on Machine Learning, 1596-1606, 2019
The many faces of robustness: A critical analysis of out-of-distribution generalization
D Hendrycks, S Basart, N Mu, S Kadavath, F Wang, E Dorundo, R Desai, ...
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
Resilience: A criterion for learning in the presence of arbitrary outliers
J Steinhardt, M Charikar, G Valiant
arXiv preprint arXiv:1703.04940, 2017
Stronger data poisoning attacks break data sanitization defenses
PW Koh, J Steinhardt, P Liang
arXiv preprint arXiv:1811.00741, 2018
Robust moment estimation and improved clustering via sum of squares
PK Kothari, J Steinhardt, D Steurer
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing …, 2018
Finite-time regional verification of stochastic non-linear systems
J Steinhardt, R Tedrake
The International Journal of Robotics Research 31 (7), 901-923, 2012
Memory, communication, and statistical queries
J Steinhardt, G Valiant, S Wager
Conference on Learning Theory, 1490-1516, 2016
Testing robustness against unforeseen adversaries
D Kang, Y Sun, D Hendrycks, T Brown, J Steinhardt
arXiv preprint arXiv:1908.08016, 2019
Adaptivity and optimism: An improved exponentiated gradient algorithm
J Steinhardt, P Liang
International Conference on Machine Learning, 1593-1601, 2014
Rethinking bias-variance trade-off for generalization of neural networks
Z Yang, Y Yu, C You, J Steinhardt, Y Ma
International Conference on Machine Learning, 10767-10777, 2020
Minimax rates for memory-bounded sparse linear regression
J Steinhardt, J Duchi
Conference on Learning Theory, 1564-1587, 2015
A benchmark for anomaly segmentation
D Hendrycks, S Basart, M Mazeika, M Mostajabi, J Steinhardt, D Song
arXiv e-prints, arXiv: 1911.11132, 2019
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