no code implementations • 7 Mar 2024 • Shengyuan Hu, Saeed Mahloujifar, Virginia Smith, Kamalika Chaudhuri, Chuan Guo
Data-dependent privacy accounting frameworks such as per-instance differential privacy (pDP) and Fisher information loss (FIL) confer fine-grained privacy guarantees for individuals in a fixed training dataset.
1 code implementation • 25 Feb 2024 • Qi Pang, Shengyuan Hu, Wenting Zheng, Virginia Smith
Advances in generative models have made it possible for AI-generated text, code, and images to mirror human-generated content in many applications.
no code implementations • 16 Feb 2023 • Shengyuan Hu, Dung Daniel Ngo, Shuran Zheng, Virginia Smith, Zhiwei Steven Wu
Federated Learning (FL) aims to foster collaboration among a population of clients to improve the accuracy of machine learning without directly sharing local data.
1 code implementation • 16 Jun 2022 • Ziyu Liu, Shengyuan Hu, Zhiwei Steven Wu, Virginia Smith
While the application of differential privacy (DP) has been well-studied in cross-device federated learning (FL), there is a lack of work considering DP and its implications for cross-silo FL, a setting characterized by a limited number of clients each containing many data subjects.
1 code implementation • 4 Apr 2022 • Shengyuan Hu, Jack Goetz, Kshitiz Malik, Hongyuan Zhan, Zhe Liu, Yue Liu
Model compression is important in federated learning (FL) with large models to reduce communication cost.
no code implementations • 18 Mar 2022 • Shengyuan Hu, Zhiwei Steven Wu, Virginia Smith
In particular, we explore and extend the notion of Bounded Group Loss as a theoretically-grounded approach for group fairness.
1 code implementation • 30 Aug 2021 • Shengyuan Hu, Zhiwei Steven Wu, Virginia Smith
Many problems in machine learning rely on multi-task learning (MTL), in which the goal is to solve multiple related machine learning tasks simultaneously.
4 code implementations • 8 Dec 2020 • Tian Li, Shengyuan Hu, Ahmad Beirami, Virginia Smith
Fairness and robustness are two important concerns for federated learning systems.
1 code implementation • NeurIPS 2019 • Tao Yu, Shengyuan Hu, Chuan Guo, Wei-Lun Chao, Kilian Q. Weinberger
Natural images are virtually surrounded by low-density misclassified regions that can be efficiently discovered by gradient-guided search --- enabling the generation of adversarial images.