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Gautam Kamath
Gautam Kamath
Other namesGautam C. Kamath
Assistant Professor @ University of Waterloo, Faculty Member @ Vector Institute
Verified email at uwaterloo.ca - Homepage
Title
Cited by
Year
Disguised Copyright Infringement of Latent Diffusion Model
Y Lu, MYR Yang, Z Liu, G Kamath, Y Yu
arXiv preprint arXiv:2404.06737, 2024
2024
Indiscriminate Data Poisoning Attacks on Pre-trained Feature Extractors
Y Lu, MYR Yang, G Kamath, Y Yu
arXiv preprint arXiv:2402.12626, 2024
2024
Distribution learnability and robustness
S Ben-David, A Bie, G Kamath, T Lechner
Advances in Neural Information Processing Systems 36, 2024
12024
Private distribution learning with public data: The view from sample compression
S Ben-David, A Bie, CL Canonne, G Kamath, V Singhal
Advances in Neural Information Processing Systems 36, 2024
62024
Not All Learnable Distribution Classes are Privately Learnable
M Bun, G Kamath, A Mouzakis, V Singhal
arXiv preprint arXiv:2402.00267, 2024
2024
Advancing differential privacy: Where we are now and future directions for real-world deployment
R Cummings, D Desfontaines, D Evans, R Geambasu, Y Huang, ...
PubPub 6 (1), 2024
28*2024
Report of the 1st Workshop on Generative AI and Law
AF Cooper, K Lee, J Grimmelmann, D Ippolito, C Callison-Burch, ...
arXiv preprint arXiv:2311.06477, 2023
12023
Avoiding Pitfalls for Privacy Accounting of Subsampled Mechanisms under Composition
CJ Lebeda, M Regehr, G Kamath
2023
A Whirlwind Introduction to Differential Privacy
G Kamath
Preface from Dr. Vivek Goel, 7, 2023
2023
Exploring the limits of model-targeted indiscriminate data poisoning attacks
Y Lu, G Kamath, Y Yu
International Conference on Machine Learning, 22856-22879, 2023
8*2023
Robustness implies privacy in statistical estimation
SB Hopkins, G Kamath, M Majid, S Narayanan
Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 497-506, 2023
312023
Choosing public datasets for private machine learning via gradient subspace distance
X Gu, G Kamath, ZS Wu
arXiv preprint arXiv:2303.01256, 2023
102023
Private gans, revisited
A Bie, G Kamath, G Zhang
arXiv preprint arXiv:2302.02936, 2023
62023
A bias-variance-privacy trilemma for statistical estimation
G Kamath, A Mouzakis, M Regehr, V Singhal, T Steinke, J Ullman
arXiv preprint arXiv:2301.13334, 2023
102023
Considerations for differentially private learning with large-scale public pretraining
F Tramèr, G Kamath, N Carlini
arXiv preprint arXiv:2212.06470, 2022
322022
Private estimation with public data
A Bie, G Kamath, V Singhal
Advances in neural information processing systems 35, 18653-18666, 2022
262022
Hidden poison: Machine unlearning enables camouflaged poisoning attacks
JZ Di, J Douglas, J Acharya, G Kamath, A Sekhari
NeurIPS ML Safety Workshop, 2022
162022
Introduction to the Special Issue on ACM-SIAM Symposium on Discrete Algorithms (SODA) 2020
G Kamath, S Assadi, A Driemel, J Kulkarni
ACM Transactions on Algorithms 18 (4), 1-2, 2022
2022
Robust estimation for random graphs
J Acharya, A Jain, G Kamath, AT Suresh, H Zhang
Conference on Learning Theory, 130-166, 2022
82022
The role of adaptive optimizers for honest private hyperparameter selection
S Mohapatra, S Sasy, X He, G Kamath, O Thakkar
Proceedings of the aaai conference on artificial intelligence 36 (7), 7806-7813, 2022
312022
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