Fowl, Liam

10 publications

CVPR 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 Baraniuk, Micah Goldblum, Tom Goldstein

ICML 2022 Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification Yuxin Wen, Jonas A. Geiping, Liam Fowl, Micah Goldblum, Tom Goldstein

CVPRW 2022 Poisons That Are Learned Faster Are More Effective Pedro Sandoval Segura, Vasu Singla, Liam Fowl, Jonas Geiping, Micah Goldblum, David Jacobs, Tom Goldstein

NeurIPS 2022 Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch Hossein Souri, Liam Fowl, Rama Chellappa, Micah Goldblum, Tom Goldstein

NeurIPS 2021 Adversarial Examples Make Strong Poisons Liam Fowl, Micah Goldblum, Ping-yeh Chiang, Jonas Geiping, Wojciech Czaja, Tom Goldstein

AAAI 2020 Adversarially Robust Distillation Micah Goldblum, Liam Fowl, Soheil Feizi, Tom Goldstein

NeurIPS 2020 Adversarially Robust Few-Shot Learning: A Meta-Learning Approach Micah Goldblum, Liam Fowl, Tom Goldstein

ECCVW 2020 Deep k-NN Defense Against Clean-Label Data Poisoning Attacks Neehar Peri, Neal Gupta, W. Ronny Huang, Liam Fowl, Chen Zhu, Soheil Feizi, Tom Goldstein, John P. Dickerson

NeurIPS 2020 MetaPoison: Practical General-Purpose Clean-Label Data Poisoning W. Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, Tom Goldstein

ICML 2020 Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein