Ping-Yeh Chiang

According to our database, Ping-Yeh Chiang authored at least 21 papers between 2019 and 2024.

Collaborative distances:

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

2024

NEFTune: Noisy Embeddings Improve Instruction Finetuning.

Neel Jain, Ping-yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Reliability of Machine Learning Models in the Real World.

Ping-Yeh Chiang

PhD thesis, 2023

Universal Pyramid Adversarial Training for Improved ViT Performance.

Ping-yeh Chiang, Yipin Zhou, Omid Poursaeed, Satya Narayan Shukla, Ashish Shah, Tom Goldstein, Ser-Nam Lim

CoRR, 2023

Baseline Defenses for Adversarial Attacks Against Aligned Language Models.

Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping-yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, Tom Goldstein

CoRR, 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

Certified Neural Network Watermarks with Randomized Smoothing.

Arpit Bansal, Ping-Yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein

Proceedings of the International Conference on Machine Learning, 2022

Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective.

Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Active Learning at the ImageNet Scale.

Zeyad Ali Sami Emam, Hong-Min Chu, Ping-Yeh Chiang, Wojciech Czaja, Richard Leapman, Micah Goldblum, Tom Goldstein

CoRR, 2021

Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release.

Liam Fowl, Ping-yeh Chiang, Micah Goldblum, Jonas Geiping, Arpit Bansal, Wojtek Czaja, Tom Goldstein

CoRR, 2021

Adversarial Examples Make Strong Poisons.

Liam Fowl, Micah Goldblum, Ping-yeh Chiang, Jonas Geiping, Wojciech Czaja, Tom Goldstein

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

ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning.

Kevin Kuo, Anthony Ostuni, Elizabeth Horishny, Michael J. Curry, Samuel Dooley, Ping-yeh Chiang, Tom Goldstein, John P. Dickerson

CoRR, 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

Detection as Regression: Certified Object Detection by Median Smoothing.

Ping-yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John P. Dickerson, 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

Certifying Strategyproof Auction Networks.

Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John Dickerson

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Detection as Regression: Certified Object Detection with Median Smoothing.

Ping-yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John Dickerson, Tom Goldstein

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 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

Compressing GANs using Knowledge Distillation.

Angeline Aguinaldo, Ping-Yeh Chiang, Alexander Gain, Ameya Patil, Kolten Pearson, Soheil Feizi

CoRR, 2019