MF mechanism consistently performs at least as well as the best prior methods.

On one hand, the local data of users may contain sensitive information, and privacy-preserving mechanisms are needed.

In contrast, in non-private settings, practitioners commonly utilize "adaptive" hyperparameter optimization methods such as Gaussian process-based optimization, which select the next candidate based on information gathered from previous outputs. This substantial contrast between private and non-private hyperparameter optimization underscores a critical concern. In our paper, we introduce DP-HyPO, a pioneering framework for "adaptive"