Seuraa
Anvith Thudi
Anvith Thudi
CS PhD, UofT
Vahvistettu sähköpostiosoite verkkotunnuksessa mail.utoronto.ca - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning
A Thudi, H Jia, I Shumailov, N Papernot
31st USENIX Security Symposium, 2021
812021
Proof-of-learning: Definitions and practice
H Jia, M Yaghini, CA Choquette-Choo, N Dullerud, A Thudi, ...
2021 IEEE Symposium on Security and Privacy (SP), 1039-1056, 2021
752021
Unrolling sgd: Understanding factors influencing machine unlearning
A Thudi, G Deza, V Chandrasekaran, N Papernot
7th IEEE European Symposium on Security and Privacy, 2021
702021
SoK: Machine learning governance
V Chandrasekaran, H Jia, A Thudi, A Travers, M Yaghini, N Papernot
arXiv preprint arXiv:2109.10870, 2021
182021
From Differential Privacy to Bounds on Membership Inference: Less can be More
A Thudi, I Shumailov, F Boenisch, N Papernot
Transactions on Machine Learning Research, 0
16*
Selective classification via neural network training dynamics
S Rabanser, A Thudi, K Hamidieh, A Dziedzic, N Papernot
arXiv preprint arXiv:2205.13532, 2022
142022
Proof-of-learning is currently more broken than you think
C Fang, H Jia, A Thudi, M Yaghini, CA Choquette-Choo, N Dullerud, ...
2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P), 797-816, 2023
13*2023
Training Private Models That Know What They Don't Know
S Rabanser, A Thudi, A Thakurta, K Dvijotham, N Papernot
37th Conference on Neural Information Processing Systems, 2023
32023
Unlearnable algorithms for in-context learning
A Muresanu, A Thudi, MR Zhang, N Papernot
arXiv preprint arXiv:2402.00751, 2024
22024
Better Sparsifiers for Directed Eulerian Graphs
S Sachdeva, A Thudi, Y Zhao
arXiv preprint arXiv:2311.06232, 2023
2023
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD
A Thudi, H Jia, C Meehan, I Shumailov, N Papernot
arXiv preprint arXiv:2307.00310, 2023
2023
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