受强制性开放获取政策约束的文章 - Preetum Nakkiran了解详情
可在其他位置公开访问的文章：13 篇
Deep double descent: Where bigger models and more data hurt
P Nakkiran, G Kaplun, Y Bansal, T Yang, B Barak, I Sutskever
International Conference on Learning Representations (ICLR) 2019, 2019
强制性开放获取政策： US National Science Foundation
SGD on Neural Networks Learns Functions of Increasing Complexity
P Nakkiran, G Kaplun, D Kalimeris, T Yang, B Edelman, H Zhang, B Barak
Advances in Neural Information Processing Systems, 3491-3501, 2019
强制性开放获取政策： US National Science Foundation
Revisiting model stitching to compare neural representations
Y Bansal, P Nakkiran, B Barak
Advances in neural information processing systems 34, 225-236, 2021
强制性开放获取政策： US National Science Foundation, US Department of Defense
The deep bootstrap framework: Good online learners are good offline generalizers
P Nakkiran, B Neyshabur, H Sedghi
International Conference on Learning Representations (ICLR) 2021, 2020
强制性开放获取政策： US National Science Foundation
Benign, tempered, or catastrophic: Toward a refined taxonomy of overfitting
N Mallinar, J Simon, A Abedsoltan, P Pandit, M Belkin, P Nakkiran
Advances in Neural Information Processing Systems 35, 1182-1195, 2022
强制性开放获取政策： US National Science Foundation
Distributional generalization: A new kind of generalization
P Nakkiran, Y Bansal
arXiv preprint arXiv:2009.08092, 2020
强制性开放获取政策： US National Science Foundation
A unifying theory of distance from calibration
J Błasiok, P Gopalan, L Hu, P Nakkiran
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 1727-1740, 2023
强制性开放获取政策： US National Science Foundation
General strong polarization
J Błasiok, V Guruswami, P Nakkiran, A Rudra, M Sudan
ACM Journal of the ACM (JACM) 69 (2), 1-67, 2022
强制性开放获取政策： US National Science Foundation, US Department of Defense
When does optimizing a proper loss yield calibration?
J Blasiok, P Gopalan, L Hu, P Nakkiran
Advances in Neural Information Processing Systems 36, 2024
强制性开放获取政策： US National Science Foundation
What you see is what you get: Principled deep learning via distributional generalization
B Kulynych, YY Yang, Y Yu, J Błasiok, P Nakkiran
Advances in Neural Information Processing Systems 35, 2168-2183, 2022
强制性开放获取政策： US National Science Foundation, Swiss National Science Foundation, US …
Knowledge Distillation: Bad Models Can Be Good Role Models
G Kaplun, E Malach, P Nakiran, S Shalev-Shwartz
Advances in Neural Information Processing Systems, 2022
强制性开放获取政策： US National Science Foundation, US Department of Energy, US Department of …
Near-Optimal NP-Hardness of Approximating Max -CSP
P Manurangsi, P Nakkiran, L Trevisan
Theory of Computing 18 (1), 1-29, 2022
强制性开放获取政策： US National Science Foundation
Optimal systematic distributed storage codes with fast encoding
P Nakkiran, KV Rashmi, K Ramchandran
2016 IEEE International Symposium on Information Theory (ISIT), 430-434, 2016
强制性开放获取政策： US National Science Foundation
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