Ping-Yeh Chiang

Publication Activity (10 Years)

Years Active: 2019-2022
Publications (10 Years): 19

Top Topics

Convex Relaxation

Top Venues

Publications

Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CVPR (2022)
Arpit Bansal, Ping-Yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein
Certified Neural Network Watermarks with Randomized Smoothing. ICML (2022)
Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CoRR (2022)
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)
Liam Fowl, Ping-Yeh Chiang, Micah Goldblum, Jonas Geiping, Arpit Bansal, Wojtek Czaja, Tom Goldstein
Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release. CoRR (2021)
Liam Fowl, Micah Goldblum, Ping-Yeh Chiang, Jonas Geiping, Wojtek Czaja, Tom Goldstein
Adversarial Examples Make Strong Poisons. CoRR (2021)
Zeyad Ali Sami Emam, Hong-Min Chu, Ping-Yeh Chiang, Wojciech Czaja, Richard Leapman, Micah Goldblum, Tom Goldstein
Active Learning at the ImageNet Scale. CoRR (2021)
Kevin Kuo, Anthony Ostuni, Elizabeth Horishny, Michael J. Curry, Samuel Dooley, Ping-Yeh Chiang, Tom Goldstein, John P. Dickerson
ProportionNet: Balancing Fairness and Revenue for Auction Design with Deep Learning. CoRR (2020)
Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John P. Dickerson
Certifying Strategyproof Auction Networks. CoRR (2020)
Michael J. Curry, Ping-Yeh Chiang, Tom Goldstein, John Dickerson
Certifying Strategyproof Auction Networks. NeurIPS (2020)
Ping-Yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John P. Dickerson, Tom Goldstein
Detection as Regression: Certified Object Detection by Median Smoothing. CoRR (2020)
Ping-Yeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studer, Tom Goldstein
Certified Defenses for Adversarial Patches. ICLR (2020)
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)
Ping-Yeh Chiang, Renkun Ni, Ahmed Abdelkader, Chen Zhu, Christoph Studer, Tom Goldstein
Certified Defenses for Adversarial Patches. CoRR (2020)
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 (2020)
Ping-Yeh Chiang, Michael J. Curry, Ahmed Abdelkader, Aounon Kumar, John Dickerson, Tom Goldstein
Detection as Regression: Certified Object Detection with Median Smoothing. NeurIPS (2020)
Renkun Ni, Hong-Min Chu, Oscar Castañeda, Ping-Yeh Chiang, Christoph Studer, Tom Goldstein
WrapNet: Neural Net Inference with Ultra-Low-Resolution Arithmetic. CoRR (2020)
Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi
WITCHcraft: Efficient PGD attacks with random step size. CoRR (2019)
Angeline Aguinaldo, Ping-Yeh Chiang, Alexander Gain, Ameya Patil, Kolten Pearson, Soheil Feizi
Compressing GANs using Knowledge Distillation. CoRR (2019)