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

von Subramani, Pranav
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 32 of 36 (2022)

Private Estimation with Public Data

von Bie, Alex
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 25 of 50 (2023)

New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma

von Kamath, Gautam
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 32 of 50 (2023)

Improved Rates for Differentially Private Stochastic Convex Optimization with Heavy-Tailed Data

von Kamath, Gautam
Veröffentlicht in International Conference on Machine Learning (39. : 2022 : Baltimore, Md.; Online) International Conference on Machine Learning (ICML 2022) ; Part 13 of 33 (2023)

PAPRIKA: PRIVATE ONLINE FALSE DISCOVERY RATE CONTROL

von ZHANG, WANRONG
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 16 of 16 (2022)

THE DISCRETE GAUSSIAN FOR DIFFERENTIAL PRIVACY

von Canonne, Clement L.
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 19 of 27 (2021)

COINPRESS: PRACTICAL PRIVATE MEAN AND COVARIANCE ESTIMATION

von Biswas, Sourav
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 18 of 27 (2021)

Social impact measurement for social enterprise

von Chang, Tzu Yang
Veröffentlicht in Entrepreneurship in Asia (2014)

DIFFERENTIALLY PRIVATE ALGORITHMS FOR LEARNING MIXTURES OF SEPARATED GAUSSIANS

von Kamath, Gautam
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 1 of 20 (2020)

Remember What You Want to Forget: Algorithms for Machine Unlearning

von Sekhari, Ayush
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 22 of 36 (2022)

PRIVATE HYPOTHESIS SELECTION

von Bun, Mark
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 1 of 20 (2020)

PRIVATELY LEARNING MARKOV RANDOM FIELDS

von Zhang, Huanyu
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 15 of 15 (2021)

Random Restrictions of High Dimensional Distributions and Uniformity Testing with Subcube Conditioning

von Canonne, Clément L.
Veröffentlicht in ACM-SIAM Symposium on Discrete Algorithms (32. : 2021 : Online) Thirty-second Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2021) ; Volume 1 of 4 (2021)

PRIVATE IDENTITY TESTING FOR HIGH-DIMENSIONAL DISTRIBUTIONS

von Canonne, Clément L.
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 13 of 27 (2021)

Special issue on SODA '20

Veröffentlicht 2022