Ping-Yeh Chiang

28 papers A* 9Misc 1Journal 17

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	NEFTune: Noisy Embeddings Improve Instruction Finetuning. ICLR 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
2023	J	`jnl`	Baseline Defenses for Adversarial Attacks Against Aligned Language Models. CoRR Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping-Yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent. ICLR Ping-Yeh Chiang, Renkun Ni, David Yu Miller, Arpit Bansal, Jonas Geiping, Micah Goldblum, Tom Goldstein
2023	J	`jnl`	NEFTune: Noisy Embeddings Improve Instruction Finetuning. CoRR 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
2023	—	`—`	Reliability of Machine Learning Models in the Real World. Ping-Yeh Chiang
2023	J	`jnl`	Universal Pyramid Adversarial Training for Improved ViT Performance. CoRR Ping-Yeh Chiang, Yipin Zhou, Omid Poursaeed, Satya Narayan Shukla, Ashish Shah, Tom Goldstein, Ser-Nam Lim
2022	A*	`conf`	Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CVPR Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein
2022	J	`jnl`	Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CoRR Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein
2022	A*	`conf`	Certified Neural Network Watermarks with Randomized Smoothing. ICML Arpit Bansal, Ping-Yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein
2022	J	`jnl`	Certified Neural Network Watermarks with Randomized Smoothing. CoRR Arpit Bansal, Ping-Yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein
2022	J	`jnl`	K-SAM: Sharpness-Aware Minimization at the Speed of SGD. CoRR Renkun Ni, Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Andrew Gordon Wilson, Tom Goldstein
2021	J	`jnl`	Active Learning at the ImageNet Scale. CoRR Zeyad Ali Sami Emam, Hong-Min Chu, Ping-Yeh Chiang, Wojciech Czaja, Richard Leapman, Micah Goldblum, Tom Goldstein
2021	A*	`conf`	Adversarial Examples Make Strong Poisons. NeurIPS Liam Fowl, Micah Goldblum, Ping-Yeh Chiang, Jonas Geiping, Wojciech Czaja, Tom Goldstein
2021	J	`jnl`	Adversarial Examples Make Strong Poisons. CoRR Liam Fowl, Micah Goldblum, Ping-Yeh Chiang, Jonas Geiping, Wojtek Czaja, Tom Goldstein
2021	J	`jnl`	Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release. CoRR Liam Fowl, Ping-Yeh Chiang, Micah Goldblum, Jonas Geiping, Arpit Bansal, Wojtek Czaja, Tom Goldstein
2021	A*	`conf`	WrapNet: Neural Net Inference with Ultra-Low-Precision Arithmetic. ICLR Renkun Ni, Hong-Min Chu, Oscar Castañeda, Ping-Yeh Chiang, Christoph Studer, Tom Goldstein
2020	A*	`conf`	Certified Defenses for Adversarial Patches. ICLR Ping-Yeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studer, Tom Goldstein
2020	J	`jnl`	Certified Defenses for Adversarial Patches. CoRR Ping-Yeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studer, Tom Goldstein
2020	A*	`conf`	Certifying Strategyproof Auction Networks. NeurIPS Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John Dickerson
2020	J	`jnl`	Certifying Strategyproof Auction Networks. CoRR Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John P. Dickerson
2020	J	`jnl`	Detection as Regression: Certified Object Detection by Median Smoothing. CoRR Ping-Yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John P. Dickerson, Tom Goldstein
2020	A*	`conf`	Detection as Regression: Certified Object Detection with Median Smoothing. NeurIPS Ping-Yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John Dickerson, Tom Goldstein
2020	J	`jnl`	Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers. CoRR Chen Zhu, Renkun Ni, Ping-Yeh Chiang, Hengduo Li, Furong Huang, Tom Goldstein
2020	J	`jnl`	ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning. CoRR Kevin Kuo, Anthony Ostuni, Elizabeth Horishny, Michael J. Curry, Samuel Dooley, Ping-Yeh Chiang, Tom Goldstein, John P. Dickerson
2020	Misc	`conf`	Witchcraft: Efficient PGD Attacks with Random Step Size. ICASSP Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi
2020	J	`jnl`	WrapNet: Neural Net Inference with Ultra-Low-Resolution Arithmetic. CoRR Renkun Ni, Hong-Min Chu, Oscar Castañeda, Ping-Yeh Chiang, Christoph Studer, Tom Goldstein
2019	J	`jnl`	Compressing GANs using Knowledge Distillation. CoRR Angeline Aguinaldo, Ping-Yeh Chiang, Alexander Gain, Ameya Patil, Kolten Pearson, Soheil Feizi
2019	J	`jnl`	WITCHcraft: Efficient PGD attacks with random step size. CoRR Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi