Anvith Thudi

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 20

Top Topics

Factors Influencing

Top Venues

USENIX Security Symposium

IEEE Symposium on Security and Privacy

Publications

Anvith Thudi, Ilia Shumailov, Franziska Boenisch, Nicolas Papernot
From Differential Privacy to Bounds on Membership Inference: Less can be More. Trans. Mach. Learn. Res. 2024 (2024)
Andrei Muresanu, Anvith Thudi, Michael R. Zhang, Nicolas Papernot
Unlearnable Algorithms for In-context Learning. CoRR (2024)
Sushant Sachdeva, Anvith Thudi, Yibin Zhao
Better Sparsifiers for Directed Eulerian Graphs. ICALP (2024)
Anvith Thudi, Chris J. Maddison
Finding Optimally Robust Data Mixtures via Concave Maximization. CoRR (2024)
Anvith Thudi, Hengrui Jia, Casey Meehan, Ilia Shumailov, Nicolas Papernot
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD. USENIX Security Symposium (2024)
Sushant Sachdeva, Anvith Thudi, Yibin Zhao
Better Sparsifiers for Directed Eulerian Graphs. CoRR (2023)
Anvith Thudi, Hengrui Jia, Casey Meehan, Ilia Shumailov, Nicolas Papernot
Gradients Look Alike: Sensitivity is Often Overestimated in DP-SGD. CoRR (2023)
Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot
Proof-of-Learning is Currently More Broken Than You Think. EuroS&P (2023)
Stephan Rabanser, Anvith Thudi, Abhradeep Guha Thakurta, Krishnamurthy Dvijotham, Nicolas Papernot
Training Private Models That Know What They Don't Know. NeurIPS (2023)
Stephan Rabanser, Anvith Thudi, Abhradeep Thakurta, Krishnamurthy Dvijotham, Nicolas Papernot
Training Private Models That Know What They Don't Know. CoRR (2023)
Anvith Thudi, Ilia Shumailov, Franziska Boenisch, Nicolas Papernot
Bounding Membership Inference. CoRR (2022)
Anvith Thudi, Hengrui Jia, Ilia Shumailov, Nicolas Papernot
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning. USENIX Security Symposium (2022)
Anvith Thudi, Gabriel Deza, Varun Chandrasekaran, Nicolas Papernot
Unrolling SGD: Understanding Factors Influencing Machine Unlearning. EuroS&P (2022)
Stephan Rabanser, Anvith Thudi, Kimia Hamidieh, Adam Dziedzic, Nicolas Papernot
Selective Classification Via Neural Network Training Dynamics. CoRR (2022)
Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot
On the Fundamental Limits of Formally (Dis)Proving Robustness in Proof-of-Learning. CoRR (2022)
Anvith Thudi, Hengrui Jia, Ilia Shumailov, Nicolas Papernot
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning. CoRR (2021)
Anvith Thudi, Gabriel Deza, Varun Chandrasekaran, Nicolas Papernot
Unrolling SGD: Understanding Factors Influencing Machine Unlearning. CoRR (2021)
Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot
Proof-of-Learning: Definitions and Practice. CoRR (2021)
Varun Chandrasekaran, Hengrui Jia, Anvith Thudi, Adelin Travers, Mohammad Yaghini, Nicolas Papernot
SoK: Machine Learning Governance. CoRR (2021)
Hengrui Jia, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Anvith Thudi, Varun Chandrasekaran, Nicolas Papernot
Proof-of-Learning: Definitions and Practice. IEEE Symposium on Security and Privacy (2021)