Resources: 

For ideas and interesting problems for the project, please check

• the list of accepted papers in TPDP 2020, TPDP 2019

• Presentations from the workshops held at Simons Institute as a part of the "Data Privacy Program" in Spring 2019.

• the list of accepted papers (related to differential privacy) in NeurIPS 2020

• the list of accepted papers (related to differential privacy) in ICML 2020.

A sample of suggested topics (optional):

• Differentially private algorithms for stochastic convex optimization (via variants of noisy SGD) . 

A sample of relevant references: [BFTT19], [FKT20], [BFGT20, Sec 6.1].

• Local (distributed) differentially private algorithms. 

A sample of relevant references: [EKP14], [BS15], [BNST17], [DKY17], [Bassily20], [CSU+19], [EFM+19],  

• Differentially private algorithms for modern/deep learning. 

A sample of relevant references: [ACG+16], [PAE+17], [BTT18], [CXX+18], [MRTZ19], [TAM19], [B-JWWG19], [TWBSC20], [VBKW20], [SVK20], [LZCW20].

• Differentially private algorithms for statistical estimation, testing and inference.

A sample of relevant references: [CKMSU19], [KLSU19], [BKSW19], [GKK+20], [CKMUZ20].