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Renkun Ni
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2020 – today
- 2024
- [c14]Renkun Ni, Yonghui Xiao, Phoenix Meadowlark, Oleg Rybakov, Tom Goldstein, Ananda Theertha Suresh, Ignacio López-Moreno, Mingqing Chen, Rajiv Mathews:
FedAQT: Accurate Quantized Training with Federated Learning. ICASSP 2024: 6100-6104 - 2023
- [c13]Ping-yeh Chiang, Renkun Ni, David Yu Miller, Arpit Bansal, Jonas Geiping, Micah Goldblum, Tom Goldstein:
Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent. ICLR 2023 - [c12]Kezhi Kong, Jiuhai Chen, John Kirchenbauer, Renkun Ni, C. Bayan Bruss, Tom Goldstein:
GOAT: A Global Transformer on Large-scale Graphs. ICML 2023: 17375-17390 - [c11]Micah Goldblum, Hossein Souri, Renkun Ni, Manli Shu, Viraj Prabhu, Gowthami Somepalli, Prithvijit Chattopadhyay, Mark Ibrahim, Adrien Bardes, Judy Hoffman, Rama Chellappa, Andrew Gordon Wilson, Tom Goldstein:
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks. NeurIPS 2023 - [i10]Micah Goldblum, Hossein Souri, Renkun Ni, Manli Shu, Viraj Prabhu, Gowthami Somepalli, Prithvijit Chattopadhyay, Mark Ibrahim, Adrien Bardes, Judy Hoffman, Rama Chellappa, Andrew Gordon Wilson, Tom Goldstein:
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks. CoRR abs/2310.19909 (2023) - 2022
- [c10]Amr Sharaf, Hal Daumé III, Renkun Ni:
Promoting Fairness in Learned Models by Learning to Active Learn under Parity Constraints. FAccT 2022: 2149-2156 - [c9]Renkun Ni, Manli Shu, Hossein Souri, Micah Goldblum, Tom Goldstein:
The Close Relationship Between Contrastive Learning and Meta-Learning. ICLR 2022 - [i9]Renkun Ni, Ping-yeh Chiang, Jonas Geiping, Micah Goldblum, Andrew Gordon Wilson, Tom Goldstein:
K-SAM: Sharpness-Aware Minimization at the Speed of SGD. CoRR abs/2210.12864 (2022) - 2021
- [j2]Yoganand Balagurunathan
, Andrew Beers, Michael F. McNitt-Gray
, Lubomir M. Hadjiiski, Sandy Napel
, Dmitry B. Goldgof
, Gustavo Pérez
, Pablo Arbeláez
, Alireza Mehrtash
, Tina Kapur
, Ehwa Yang, Jung Won Moon, Gabriel Bernardino Perez
, Ricard Delgado-Gonzalo
, Mohammad Mehdi Farhangi, Amir A. Amini
, Renkun Ni, Xue Feng
, Aditya Bagari, Kiran Vaidhya, Benjamin Veasey
, Wiem Safta, Hichem Frigui, Joseph Enguehard, Ali Gholipour
, Laura Silvana Castillo, Laura Alexandra Daza, Paul F. Pinsky, Jayashree Kalpathy-Cramer, Keyvan Farahani:
Lung Nodule Malignancy Prediction in Sequential CT Scans: Summary of ISBI 2018 Challenge. IEEE Trans. Medical Imaging 40(12): 3748-3761 (2021) - [c8]Renkun Ni, Hong-Min Chu, Oscar Castañeda, Ping-yeh Chiang, Christoph Studer, Tom Goldstein:
WrapNet: Neural Net Inference with Ultra-Low-Precision Arithmetic. ICLR 2021 - [c7]Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein:
Data Augmentation for Meta-Learning. ICML 2021: 8152-8161 - [c6]Chen Zhu, Renkun Ni, Zheng Xu, Kezhi Kong, W. Ronny Huang, Tom Goldstein:
GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training. NeurIPS 2021: 16410-16422 - [i8]Chen Zhu, Renkun Ni, Zheng Xu, Kezhi Kong, W. Ronny Huang, Tom Goldstein:
GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training. CoRR abs/2102.08098 (2021) - 2020
- [c5]Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi:
Witchcraft: Efficient PGD Attacks with Random Step Size. ICASSP 2020: 3747-3751 - [c4]Ping-yeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studer, Tom Goldstein:
Certified Defenses for Adversarial Patches. ICLR 2020 - [c3]Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein:
Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks. ICML 2020: 3607-3616 - [i7]Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein:
Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks. CoRR abs/2002.06753 (2020) - [i6]Chen Zhu, Renkun Ni, Ping-Yeh Chiang, Hengduo Li, Furong Huang, Tom Goldstein:
Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers. CoRR abs/2002.09766 (2020) - [i5]Ping-yeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studer, Tom Goldstein:
Certified Defenses for Adversarial Patches. CoRR abs/2003.06693 (2020) - [i4]Renkun Ni, Hong-Min Chu, Oscar Castañeda, Ping-yeh Chiang, Christoph Studer, Tom Goldstein:
WrapNet: Neural Net Inference with Ultra-Low-Resolution Arithmetic. CoRR abs/2007.13242 (2020) - [i3]Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein:
Data Augmentation for Meta-Learning. CoRR abs/2010.07092 (2020)
2010 – 2019
- 2019
- [j1]Yinpeng Dong, Renkun Ni, Jianguo Li, Yurong Chen, Hang Su, Jun Zhu:
Stochastic Quantization for Learning Accurate Low-Bit Deep Neural Networks. Int. J. Comput. Vis. 127(11-12): 1629-1642 (2019) - [i2]Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi:
WITCHcraft: Efficient PGD attacks with random step size. CoRR abs/1911.07989 (2019) - 2017
- [c2]Yinpeng Dong, Jianguo Li, Renkun Ni:
Learning Accurate Low-Bit Deep Neural Networks with Stochastic Quantization. BMVC 2017 - [i1]Yinpeng Dong, Renkun Ni, Jianguo Li, Yurong Chen, Jun Zhu, Hang Su:
Learning Accurate Low-Bit Deep Neural Networks with Stochastic Quantization. CoRR abs/1708.01001 (2017) - 2016
- [c1]Renkun Ni, Quanquan Gu:
Optimal Statistical and Computational Rates for One Bit Matrix Completion. AISTATS 2016: 426-434
Coauthor Index
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last updated on 2024-08-07 21:34 CEST by the dblp team
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