Renkun Ni
Renkun Ni
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Cited by
Cited by
Certified defenses for adversarial patches
P Chiang, R Ni, A Abdelkader, C Zhu, C Studer, T Goldstein
arXiv preprint arXiv:2003.06693, 2020
Data augmentation for meta-learning
R Ni, M Goldblum, A Sharaf, K Kong, T Goldstein
International Conference on Machine Learning, 8152-8161, 2021
Learning accurate low-bit deep neural networks with stochastic quantization
Y Dong, R Ni, J Li, Y Chen, J Zhu, H Su
arXiv preprint arXiv:1708.01001, 2017
Unraveling meta-learning: Understanding feature representations for few-shot tasks
M Goldblum, S Reich, L Fowl, R Ni, V Cherepanova, T Goldstein
International Conference on Machine Learning, 3607-3616, 2020
Gradinit: Learning to initialize neural networks for stable and efficient training
C Zhu, R Ni, Z Xu, K Kong, WR Huang, T Goldstein
Advances in Neural Information Processing Systems 34, 16410-16422, 2021
Automatic segmentation of all lower limb muscles from high-resolution magnetic resonance imaging using a cascaded three-dimensional deep convolutional neural network
R Ni, CH Meyer, SS Blemker, JM Hart, X Feng
Journal of Medical Imaging 6 (4), 044009-044009, 2019
Wrapnet: Neural net inference with ultra-low-precision arithmetic
R Ni, H Chu, O Castañeda Fernández, P Chiang, C Studer, T Goldstein
International Conference on Learning Representations ICLR 2021, 2021
Optimal statistical and computational rates for one bit matrix completion
R Ni, Q Gu
Artificial Intelligence and Statistics, 426-434, 2016
GOAT: A global transformer on large-scale graphs
K Kong, J Chen, J Kirchenbauer, R Ni, CB Bruss, T Goldstein
International Conference on Machine Learning, 17375-17390, 2023
Promoting fairness in learned models by learning to active learn under parity constraints
A Sharaf, H Daume III, R Ni
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
Lung nodule malignancy prediction in sequential ct scans: Summary of isbi 2018 challenge
Y Balagurunathan, A Beers, M Mcnitt-Gray, L Hadjiiski, S Napel, ...
IEEE transactions on medical imaging 40 (12), 3748-3761, 2021
The Close Relationship Between Contrastive Learning and Meta-Learning
R Ni, M Shu, H Souri, M Goldblum, T Goldstein
International Conference on Learning Representations, 2021
Loss landscapes are all you need: Neural network generalization can be explained without the implicit bias of gradient descent
P Chiang, R Ni, DY Miller, A Bansal, J Geiping, M Goldblum, T Goldstein
The Eleventh International Conference on Learning Representations, 2022
Efficient neural networks with elaborate matrix structures in machine learning environments
Y Chen, J Li, R Ni
US Patent App. 16/632,145, 2020
Witchcraft: Efficient PGD attacks with random step size
PY Chiang, J Geiping, M Goldblum, T Goldstein, R Ni, S Reich, A Shafahi
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
Battle of the backbones: A large-scale comparison of pretrained models across computer vision tasks
M Goldblum, H Souri, R Ni, M Shu, V Prabhu, G Somepalli, ...
Advances in Neural Information Processing Systems 36, 2024
Quantitative relationships between individual lower-limb muscle volumes and jump and sprint performances of basketball players
T Xie, KB Crump, R Ni, CH Meyer, JM Hart, SS Blemker, X Feng
The Journal of Strength & Conditioning Research 34 (3), 623-631, 2020
K-sam: Sharpness-aware minimization at the speed of sgd
R Ni, P Chiang, J Geiping, M Goldblum, AG Wilson, T Goldstein
arXiv preprint arXiv:2210.12864, 2022
System and method for automatic segmentation of muscles from high-resolution MRI using 3D deep convolutional neural network
X Feng, R Ni, A Konda, SS Blemker, JM Hart, CH Meyer
US Patent 11,526,993, 2022
Improving the tightness of convex relaxation bounds for training certifiably robust classifiers
C Zhu, R Ni, P Chiang, H Li, F Huang, T Goldstein
arXiv preprint arXiv:2002.09766, 2020
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