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Micah Goldblum
Micah Goldblum
Columbia University
columbia.edu üzerinde doğrulanmış e-posta adresine sahip - Ana Sayfa
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
A Cookbook of Self-Supervised Learning
R Balestriero, M Ibrahim, V Sobal, A Morcos, S Shekhar, T Goldstein, ...
arXiv preprint arXiv:2304.12210, 2023
486*2023
Dataset security for machine learning: Data poisoning, backdoor attacks, and defenses
M Goldblum, D Tsipras, C Xie, ...
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2022, 2022
382*2022
Saint: Improved neural networks for tabular data via row attention and contrastive pre-training
G Somepalli, M Goldblum, A Schwarzschild, CB Bruss, T Goldstein
arXiv preprint arXiv:2106.01342, 2021
380*2021
Baseline defenses for adversarial attacks against aligned language models
N Jain, A Schwarzschild, Y Wen, G Somepalli, J Kirchenbauer, P Chiang, ...
arXiv preprint arXiv:2309.00614, 2023
311*2023
Diffusion art or digital forgery? investigating data replication in diffusion models
G Somepalli, V Singla, M Goldblum, J Geiping, T Goldstein
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
3072023
The Intrinsic Dimension of Images and Its Impact on Learning
P Pope, C Zhu, A Abdelkader, M Goldblum, T Goldstein
International Conference on Learning Representations (ICLR) 2021, 2021
2882021
Cold diffusion: Inverting arbitrary image transforms without noise
A Bansal, E Borgnia, HM Chu, JS Li, H Kazemi, F Huang, M Goldblum, ...
Advances in Neural Information Processing Systems (NeurIPS), 2023
2662023
Universal guidance for diffusion models
A Bansal, HM Chu, A Schwarzschild, S Sengupta, M Goldblum, J Geiping, ...
The Twelfth International Conference on Learning Representations (ICLR) 2024, 2024
254*2024
Adversarially Robust Distillation
M Goldblum, L Fowl, S Feizi, T Goldstein
AAAI Conference on Artificial Intelligence (AAAI) 2020, 2020
2512020
Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery
Y Wen, N Jain, J Kirchenbauer, M Goldblum, J Geiping, T Goldstein
Advances in Neural Information Processing Systems 36, 2023
2312023
Just how toxic is data poisoning? a unified benchmark for backdoor and data poisoning attacks
A Schwarzschild*, M Goldblum*, A Gupta, JP Dickerson, T Goldstein
International Conference on Machine Learning (ICML) 2021, 2021
2022021
Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff
E Borgnia, V Cherepanova, L Fowl, A Ghiasi, J Geiping, M Goldblum, ...
International Conference on Acoustics, Speech, and Signal Processing (ICASSP …, 2021
179*2021
On the Reliability of Watermarks for Large Language Models
J Kirchenbauer, J Geiping, Y Wen, M Shu, K Saifullah, K Kong, ...
The Twelfth International Conference on Learning Representations (ICLR) 2024, 2024
161*2024
LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition
V Cherepanova, M Goldblum, H Foley, S Duan, J Dickerson, G Taylor, ...
International Conference on Learning Representations (ICLR) 2021, 2021
1552021
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
L Fowl, J Geiping, W Czaja, M Goldblum, T Goldstein
International Conference on Learning Representations (ICLR) 2022, 2022
1542022
When Do Neural Nets Outperform Boosted Trees on Tabular Data?
D McElfresh, S Khandagale, J Valverde, G Ramakrishnan, M Goldblum, ...
Advances in Neural Information Processing Systems (NeurIPS), 2023
145*2023
Adversarial Examples Make Strong Poisons
L Fowl*, M Goldblum*, P Chiang, J Geiping, W Czaja, T Goldstein
Advances in Neural Information Processing Systems (NeurIPS), 2021
1392021
Sleeper agent: Scalable hidden trigger backdoors for neural networks trained from scratch
H Souri, L Fowl, R Chellappa, M Goldblum, T Goldstein
Advances in Neural Information Processing Systems (NeurIPS) 35, 19165-19178, 2022
1372022
Towards transferable adversarial attacks on image and video transformers
Z Wei, J Chen, M Goldblum, Z Wu, T Goldstein, YG Jiang, LS Davis
IEEE Transactions on Image Processing 32, 6346-6358, 2023
132*2023
Data Augmentation for Meta-Learning
R Ni, M Goldblum, A Sharaf, K Kong, T Goldstein
International Conference on Machine Learning (ICML) 2021, 2021
1062021
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