Liam Fowl

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 38

Top Topics

Transfer Learning

Feature Representations

Top Venues

Publications

Hossein Souri, Arpit Bansal, Hamid Kazemi, Liam Fowl, Aniruddha Saha, Jonas Geiping, Andrew Gordon Wilson, Rama Chellappa, Tom Goldstein, Micah Goldblum
Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion. CoRR (2024)
Beltrán Labrador, Guanlong Zhao, Ignacio López-Moreno, Angelo Scorza Scarpati, Liam Fowl, Quan Wang
Exploring Sequence-to-Sequence Transformer-Transducer Models for Keyword Spotting. ICASSP (2023)
Harrison Foley, Liam Fowl, Tom Goldstein, Gavin Taylor
Execute Order 66: Targeted Data Poisoning for Reinforcement Learning. CoRR (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. CVPR (2022)
Beltrán Labrador, Guanlong Zhao, Ignacio López-Moreno, Angelo Scorza Scarpati, Liam Fowl, Quan Wang
Exploring Sequence-to-Sequence Transformer-Transducer Models for Keyword Spotting. CoRR (2022)
Yuxin Wen, Jonas Geiping, Liam Fowl, Micah Goldblum, Tom Goldstein
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification. CoRR (2022)
Yuxin Wen, Jonas Geiping, Liam Fowl, Hossein Souri, Rama Chellappa, Micah Goldblum, Tom Goldstein
Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning. CoRR (2022)
Liam Fowl, Jonas Geiping, Steven Reich, Yuxin Wen, Wojtek Czaja, Micah Goldblum, Tom Goldstein
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models. CoRR (2022)
Hossein Souri, Liam Fowl, Rama Chellappa, Micah Goldblum, Tom Goldstein
Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch. NeurIPS (2022)
Pedro Sandoval Segura, Vasu Singla, Liam Fowl, Jonas Geiping, Micah Goldblum, David Jacobs, Tom Goldstein
Poisons that are learned faster are more effective. CVPR Workshops (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)
Pedro Sandoval Segura, Vasu Singla, Liam Fowl, Jonas Geiping, Micah Goldblum, David Jacobs, Tom Goldstein
Poisons that are learned faster are more effective. CoRR (2022)
Yuxin Wen, Jonas Geiping, Liam Fowl, Micah Goldblum, Tom Goldstein
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification. ICML (2022)
Liam Fowl, Jonas Geiping, Wojtek Czaja, Micah Goldblum, Tom Goldstein
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models. CoRR (2021)
Liam Fowl, Micah Goldblum, Ping-yeh Chiang, Jonas Geiping, Wojciech Czaja, Tom Goldstein
Adversarial Examples Make Strong Poisons. NeurIPS (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)
Hossein Souri, Micah Goldblum, Liam Fowl, Rama Chellappa, Tom Goldstein
Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch. CoRR (2021)
Liam Fowl, Micah Goldblum, Ping-Yeh Chiang, Jonas Geiping, Wojtek Czaja, Tom Goldstein
Adversarial Examples Make Strong Poisons. CoRR (2021)
Jonas Geiping, Liam Fowl, Gowthami Somepalli, Micah Goldblum, Michael Moeller, Tom Goldstein
What Doesn't Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors. CoRR (2021)
Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta
Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. ICASSP (2021)
Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein
DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations. CoRR (2021)
Ahmed Abdelkader, Michael J. Curry, Liam Fowl, Tom Goldstein, Avi Schwarzschild, Manli Shu, Christoph Studer, Chen Zhu
Headless Horseman: Adversarial Attacks on Transfer Learning Models. ICASSP (2020)
W. Ronny Huang, Zeyad Emam, Micah Goldblum, Liam Fowl, Justin K. Terry, Furong Huang, Tom Goldstein
Understanding Generalization Through Visualizations. ICBINB@NeurIPS (2020)
Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein
Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks. ICML (2020)
Micah Goldblum, Liam Fowl, Tom Goldstein
Adversarially Robust Few-Shot Learning: A Meta-Learning Approach. NeurIPS (2020)
W. Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, Tom Goldstein
MetaPoison: Practical General-purpose Clean-label Data Poisoning. CoRR (2020)
Micah Goldblum, Steven Reich, Liam Fowl, Renkun Ni, Valeriia Cherepanova, Tom Goldstein
Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks. CoRR (2020)
Liam Fowl, Micah Goldblum, Arjun Gupta, Amr Sharaf, Tom Goldstein
Random Network Distillation as a Diversity Metric for Both Image and Text Generation. CoRR (2020)
Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta
Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. CoRR (2020)
Micah Goldblum, Liam Fowl, Soheil Feizi, Tom Goldstein
Adversarially Robust Distillation. AAAI (2020)
Jonas Geiping, Liam Fowl, W. Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching. CoRR (2020)
W. Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, Tom Goldstein
MetaPoison: Practical General-purpose Clean-label Data Poisoning. NeurIPS (2020)
Neehar Peri, Neal Gupta, W. Ronny Huang, Liam Fowl, Chen Zhu, Soheil Feizi, Tom Goldstein, John P. Dickerson
Deep k-NN Defense Against Clean-Label Data Poisoning Attacks. ECCV Workshops (1) (2020)
Ahmed Abdelkader, Michael J. Curry, Liam Fowl, Tom Goldstein, Avi Schwarzschild, Manli Shu, Christoph Studer, Chen Zhu
Headless Horseman: Adversarial Attacks on Transfer Learning Models. CoRR (2020)
Neal Gupta, W. Ronny Huang, Liam Fowl, Chen Zhu, Soheil Feizi, Tom Goldstein, John P. Dickerson
Strong Baseline Defenses Against Clean-Label Poisoning Attacks. CoRR (2019)
W. Ronny Huang, Zeyad Emam, Micah Goldblum, Liam Fowl, Justin K. Terry, Furong Huang, Tom Goldstein
Understanding Generalization through Visualizations. CoRR (2019)
Micah Goldblum, Liam Fowl, Tom Goldstein
Robust Few-Shot Learning with Adversarially Queried Meta-Learners. CoRR (2019)
Micah Goldblum, Liam Fowl, Soheil Feizi, Tom Goldstein
Adversarially Robust Distillation. CoRR (2019)