Yulian Wu

h-index

Research activity per year

Fingerprint

Dive into the research topics where Yulian Wu is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

1 Similar Profiles

3 Paper
1 Conference contribution
1 Article

PPML-Omics: A privacy-preserving federated machine learning method protects patients’ privacy in omic data
Zhou, J., Chen, S., Wu, Y., Li, H., Zhang, B., Zhou, L., Hu, Y., Xiang, Z., Li, Z., Chen, N., Han, W., Xu, C., Wang, D. & Gao, X., Feb 2024, In: SCIENCE ADVANCES. 10, 5
Research output: Contribution to journal › Article › peer-review

Open Access
9 Scopus citations
Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards
Wu, Y., Zhou, X., Chowdhury, S. R. & Wang, D., 2023, p. 37880-37918. 39 p.
Research output: Contribution to conference › Paper › peer-review
1 Scopus citations
On Private and Robust Bandits
Wu, Y., Tao, Y., Zhou, X. & Wang, D., 2023.
Research output: Contribution to conference › Paper › peer-review
Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits
Tao, Y., Wu, Y., Zhao, P. & Wang, D., 2022, p. 1546-1574. 29 p.
Research output: Contribution to conference › Paper › peer-review
7 Scopus citations
Private Stochastic Convex Optimization and Sparse Learning with Heavy-tailed Data Revisited
Tao, Y., Wu, Y., Cheng, X. & Wang, D., 2022, Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022. De Raedt, L. & De Raedt, L. (eds.). International Joint Conferences on Artificial Intelligence Organization, p. 3947-3953 7 p. (IJCAI International Joint Conference on Artificial Intelligence).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Open Access
6 Scopus citations

Findings on Machine Learning Discussed by Investigators at King Abdullah University of Science and Technology (KAUST) (Ppml-omics: a Privacy-preserving Federated Machine Learning Method Protects Patients' Privacy In Omic Data)
Gao, X., Han, W., Li, Z., Zhou, L., Zhang, B., Wang, D., Zhou, J., Chen, S. & Wu, Y.
05/3/24
1 item of Media coverage
Press/Media: Press / Media
Revolutionizing Medical Research: Scientists Develop Groundbreaking Privacy-Preserving AI
Gao, X. & Wu, Y.
03/5/24
2 items of Media coverage
Press/Media: Press / Media

Yulian Wu

Fingerprint

Collaborations and top research areas from the last five years

Dive into details

PPML-Omics: A privacy-preserving federated machine learning method protects patients’ privacy in omic data

Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards

On Private and Robust Bandits

Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits

Private Stochastic Convex Optimization and Sparse Learning with Heavy-tailed Data Revisited

Findings on Machine Learning Discussed by Investigators at King Abdullah University of Science and Technology (KAUST) (Ppml-omics: a Privacy-preserving Federated Machine Learning Method Protects Patients' Privacy In Omic Data)

Revolutionizing Medical Research: Scientists Develop Groundbreaking Privacy-Preserving AI

Yulian Wu

Fingerprint

Collaborations and top research areas from the last five years

Research output

PPML-Omics: A privacy-preserving federated machine learning method protects patients’ privacy in omic data

Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards

On Private and Robust Bandits

Optimal Rates of (Locally) Differentially Private Heavy-tailed Multi-Armed Bandits

Private Stochastic Convex Optimization and Sparse Learning with Heavy-tailed Data Revisited

Press/Media

Findings on Machine Learning Discussed by Investigators at King Abdullah University of Science and Technology (KAUST) (Ppml-omics: a Privacy-preserving Federated Machine Learning Method Protects Patients' Privacy In Omic Data)

Revolutionizing Medical Research: Scientists Develop Groundbreaking Privacy-Preserving AI