An Optimal and Scalable Matrix Mechanism for Noisy Marginals under Convex Loss Functions

1 code implementation • NeurIPS 2023 • Yingtai Xiao, Guanlin He, Danfeng Zhang, Daniel Kifer

Noisy marginals are a common form of confidentiality-protecting data release and are useful for many downstream tasks such as contingency table analysis, construction of Bayesian networks, and even synthetic data generation.

Synthetic Data Generation

Answering Private Linear Queries Adaptively using the Common Mechanism

1 code implementation • 30 Nov 2022 • Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer

Since M* will be used no matter what, the analyst can use its output to decide whether to subsequently run M1'(thus recreating the analysis supported by M1) or M2'(recreating the analysis supported by M2), without wasting privacy loss budget.

Optimizing Fitness-For-Use of Differentially Private Linear Queries

1 code implementation • 30 Nov 2020 • Yingtai Xiao, Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer

In practice, differentially private data releases are designed to support a variety of applications.

Databases

Bandit Learning for Diversified Interactive Recommendation

no code implementations • 1 Jul 2019 • Yong Liu, Yingtai Xiao, Qiong Wu, Chunyan Miao, Juyong Zhang

Interactive recommender systems that enable the interactions between users and the recommender system have attracted increasing research attentions.

Bayesian Inference Recommendation Systems +1