Gautam Kamath

papers

1,173

total citations

papers (14)

Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization

NEURIPS 2021arXiv

citations

Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks

NEURIPS 2023arXiv

citations

Private Identity Testing for High-Dimensional Distributions

NEURIPS 2020arXiv

citations

New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma

NEURIPS 2022arXiv

citations

Private Estimation with Public Data

NEURIPS 2022arXiv

citations

Machine Unlearning Fails to Remove Data Poisoning Attacks

ICLR 2025arXiv

citations

Private Distribution Learning with Public Data: The View from Sample Compression

NEURIPS 2023arXiv

citations

Disguised Copyright Infringement of Latent Diffusion Models

ICML 2024arXiv

citations

Differentially Private Post-Processing for Fair Regression

ICML 2024arXiv

citations

Distribution Learnability and Robustness

NEURIPS 2023arXiv

citations

Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining

ICML 2024

citations

Gautam Kamath

papers (14)

Remember What You Want to Forget: Algorithms for Machine Unlearning

The Discrete Gaussian for Differential Privacy

CoinPress: Practical Private Mean and Covariance Estimation

Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization

Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks

Private Identity Testing for High-Dimensional Distributions

New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma

Private Estimation with Public Data

Machine Unlearning Fails to Remove Data Poisoning Attacks

Private Distribution Learning with Public Data: The View from Sample Compression

Disguised Copyright Infringement of Latent Diffusion Models

Differentially Private Post-Processing for Fair Regression

Distribution Learnability and Robustness

Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining

papers (14)

Remember What You Want to Forget: Algorithms for Machine Unlearning

The Discrete Gaussian for Differential Privacy

CoinPress: Practical Private Mean and Covariance Estimation

Enabling Fast Differentially Private SGD via Just-in-Time Compilation and Vectorization

Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks

Private Identity Testing for High-Dimensional Distributions

New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma

Private Estimation with Public Data

Machine Unlearning Fails to Remove Data Poisoning Attacks

Private Distribution Learning with Public Data: The View from Sample Compression

Disguised Copyright Infringement of Latent Diffusion Models

Differentially Private Post-Processing for Fair Regression

Distribution Learnability and Robustness

Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining