Rachel Redberg

According to our database, Rachel Redberg authored at least 7 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Privacy Profiles for Private Selection.

Antti Koskela, Rachel Redberg, Yu-Xiang Wang

CoRR, 2024

2023

Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy.

Yingyu Lin, Yian Ma, Yu-Xiang Wang, Rachel Redberg

CoRR, 2023

Improving the Privacy and Practicality of Objective Perturbation for Differentially Private Linear Learners.

Rachel Redberg, Antti Koskela, Yu-Xiang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Generalized PTR: User-Friendly Recipes for Data-Adaptive Algorithms with Differential Privacy.

Rachel Redberg, Yuqing Zhu, Yu-Xiang Wang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Differentially Private Linear Sketches: Efficient Implementations and Applications.

Fuheng Zhao, Dan Qiao, Rachel Redberg, Divyakant Agrawal, Amr El Abbadi, Yu-Xiang Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Tree++: Truncated Tree Based Graph Kernels.

Wei Ye, Zhen Wang, Rachel Redberg, Ambuj K. Singh

IEEE Trans. Knowl. Data Eng., 2021

Privately Publishable Per-instance Privacy.

Rachel Redberg, Yu-Xiang Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021