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Kristian Georgiev
Kristian Georgiev
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Title
Cited by
Cited by
Year
Trak: Attributing model behavior at scale
SM Park, K Georgiev, A Ilyas, G Leclerc, A Madry
arXiv preprint arXiv:2303.14186, 2023
622023
Privacy induces robustness: Information-computation gaps and sparse mean estimation
K Georgiev, S Hopkins
Advances in neural information processing systems 35, 6829-6842, 2022
212022
On the convergence theory of debiased model-agnostic meta-reinforcement learning
A Fallah, K Georgiev, A Mokhtari, A Ozdaglar
Advances in Neural Information Processing Systems 34, 3096-3107, 2021
212021
Implicit bias of linear equivariant networks
H Lawrence, K Georgiev, A Dienes, BT Kiani
arXiv preprint arXiv:2110.06084, 2021
142021
The journey, not the destination: How data guides diffusion models
K Georgiev, J Vendrow, H Salman, SM Park, A Madry
arXiv preprint arXiv:2312.06205, 2023
72023
Rethinking backdoor attacks
A Khaddaj, G Leclerc, A Makelov, K Georgiev, H Salman, A Ilyas, A Madry
International Conference on Machine Learning, 16216-16236, 2023
72023
Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection
S Jain, K Hamidieh, K Georgiev, A Ilyas, M Ghassemi, A Madry
arXiv preprint arXiv:2406.16846, 2024
2024
pnnl/projection_ntk
K Georgiev, A Engel, S Park, G Leclerc, A Ilyas, B Cohen-Wang, G Tanadi, ...
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States), 2023
2023
Data Attribution: From Classifiers to Generative Models
K Georgiev
Massachusetts Institute of Technology, 2023
2023
ContextCite: Attributing Model Generation to Context
B Cohen-Wang, H Shah, K Georgiev, A Madry
ICML 2024 Workshop on Foundation Models in the Wild, 0
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Articles 1–10