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Brian Axelrod
Brian Axelrod
Zweryfikowany adres z cs.stanford.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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Provably Safe Robot Navigation with Obstacle Uncertainty
B Axelrod, LP Kaelbling, T Lozano-Pérez
Robotics Science and Systems 13, 2017
732017
Causal strategic linear regression
Y Shavit, B Edelman, B Axelrod
International Conference on Machine Learning, 8676-8686, 2020
602020
Near-optimal approximate discrete and continuous submodular function minimization
B Axelrod, YP Liu, A Sidford
Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete …, 2020
262020
Sample amplification: Increasing dataset size even when learning is impossible
B Axelrod, S Garg, V Sharan, G Valiant
International Conference on Machine Learning, 442-451, 2020
142020
Hardness of 3d motion planning under obstacle uncertainty
L Shimanuki, B Axelrod
International Workshop on the Algorithmic Foundations of Robotics, 852-867, 2018
142018
Learning from strategic agents: Accuracy, improvement, and causality
Y Shavit, B Edelman, B Axelrod
arXiv preprint arXiv:2002.10066, 2020
122020
A polynomial time algorithm for log-concave maximum likelihood via locally exponential families
B Axelrod, I Diakonikolas, A Stewart, A Sidiropoulos, G Valiant
Advances in Neural Information Processing Systems 32, 2019
122019
Hardness of motion planning with obstacle uncertainty in two dimensions
L Shimanuki, B Axelrod
The International Journal of Robotics Research 40 (10-11), 1151-1166, 2021
62021
Algorithms for safe robot navigation
BM Axelrod
Massachusetts Institute of Technology, 2017
62017
USE-evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging
S Ostmeier, B Axelrod, F Isensee, J Bertels, M Mlynash, S Christensen, ...
Medical Image Analysis 90, 102927, 2023
42023
An efficient algorithm for high-dimensional log-concave maximum likelihood
B Axelrod, G Valiant
arXiv preprint arXiv:1811.03204, 2018
42018
On the statistical complexity of sample amplification
B Axelrod, S Garg, Y Han, V Sharan, G Valiant
arXiv preprint arXiv:2201.04315, 2022
32022
Reducing FPGA algorithm area by avoiding redundant computation
B Axelrod, M Laverne
2015 IEEE International Conference on Robotics and Automation (ICRA), 503-508, 2015
32015
Random expert sampling for deep learning segmentation of acute ischemic stroke on non-contrast CT
S Ostmeier, B Axelrod, Y Liu, Y Yu, B Jiang, N Yuen, B Pulli, ...
Journal of NeuroInterventional Surgery, 2024
12024
Non-inferiority of deep learning ischemic stroke segmentation on non-contrast CT within 16-hours compared to expert neuroradiologists
S Ostmeier, B Axelrod, BFJ Verhaaren, S Christensen, A Mahammedi, ...
Scientific Reports 13 (1), 16153, 2023
12023
Non-inferiority of Deep Learning Acute Ischemic Stroke Segmentation on Non-Contrast CT Compared to Expert Neuroradiologists
S Ostmeier, B Axelrod, BFJ Verhaaren, S Christensen, A Mahammedi, ...
arXiv preprint arXiv:2211.15341, 2022
12022
Learning From Strategic Agents: Accuracy, Improvement, and Causality, ICML
Y Shavit, B Edelman, B Axelrod
Proceedings of Machine Learning Research, 2020
12020
Efficient Motion Planning Under Obstacle Uncertainty with Local Dependencies
B Axelrod, L Shimanuki
International Workshop on the Algorithmic Foundations of Robotics, 68-84, 2022
2022
Sidestepping Hardness in Statistical Problems
B Axelrod
Stanford University, 2022
2022
Sample Amplification: Increasing Dataset Size even when Learning is Impossible, ICML
B Axelrod, S Garg, V Sharan, V Gregory
Proceedings of Machine Learning Research, 2020
2020
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