Renkun Ni

According to our database, Renkun Ni authored at least 19 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GOAT: A Global Transformer on Large-scale Graphs.

Kezhi Kong, Jiuhai Chen, John Kirchenbauer, Renkun Ni, C. Bayan Bruss, Tom Goldstein

Proceedings of the International Conference on Machine Learning, 2023

Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent.

Ping-yeh Chiang, Renkun Ni, David Yu Miller, Arpit Bansal, Jonas Geiping, Micah Goldblum, Tom Goldstein

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

K-SAM: Sharpness-Aware Minimization at the Speed of SGD.

Renkun Ni, Ping-yeh Chiang, Jonas Geiping, Micah Goldblum, Andrew Gordon Wilson, Tom Goldstein

CoRR, 2022

The Close Relationship Between Contrastive Learning and Meta-Learning.

Renkun Ni, Manli Shu, Hossein Souri, Micah Goldblum, Tom Goldstein

Proceedings of the Tenth International Conference on Learning Representations, 2022

Promoting Fairness in Learned Models by Learning to Active Learn under Parity Constraints.

Amr Sharaf, Hal Daumé III, Renkun Ni

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021

Lung Nodule Malignancy Prediction in Sequential CT Scans: Summary of ISBI 2018 Challenge.

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

IEEE Trans. Medical Imaging, 2021

GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training.

Chen Zhu, Renkun Ni, Zheng Xu, Kezhi Kong, W. Ronny Huang, Tom Goldstein

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Data Augmentation for Meta-Learning.

Renkun Ni, Micah Goldblum, Amr Sharaf, Kezhi Kong, Tom Goldstein

Proceedings of the 38th International Conference on Machine Learning, 2021

WrapNet: Neural Net Inference with Ultra-Low-Precision Arithmetic.

Renkun Ni, Hong-Min Chu, Oscar Castañeda, Ping-yeh Chiang, Christoph Studer, Tom Goldstein

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

WrapNet: Neural Net Inference with Ultra-Low-Resolution Arithmetic.

Renkun Ni, Hong-Min Chu, Oscar Castañeda, Ping-yeh Chiang, Christoph Studer, Tom Goldstein

CoRR, 2020

Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers.

Chen Zhu, Renkun Ni, Ping-Yeh Chiang, Hengduo Li, Furong Huang, Tom Goldstein

CoRR, 2020

Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks.

Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein

Proceedings of the 37th International Conference on Machine Learning, 2020

Certified Defenses for Adversarial Patches.

Ping-yeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studer, Tom Goldstein

Proceedings of the 8th International Conference on Learning Representations, 2020

Witchcraft: Efficient PGD Attacks with Random Step Size.

Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Stochastic Quantization for Learning Accurate Low-Bit Deep Neural Networks.

Yinpeng Dong, Renkun Ni, Jianguo Li, Yurong Chen, Hang Su, Jun Zhu

Int. J. Comput. Vis., 2019

2017

Learning Accurate Low-Bit Deep Neural Networks with Stochastic Quantization.

Yinpeng Dong, Renkun Ni, Jianguo Li, Yurong Chen, Jun Zhu, Hang Su

CoRR, 2017

Learning Accurate Low-Bit Deep Neural Networks with Stochastic Quantization.

Yinpeng Dong, Jianguo Li, Renkun Ni

Proceedings of the British Machine Vision Conference 2017, 2017

2016

Optimal Statistical and Computational Rates for One Bit Matrix Completion.

Renkun Ni, Quanquan Gu

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016