Smart glasses privacy concerns prompt Android app Nearby Glasses by Yves Jeanrenaud that detects hidden cameras by scanning Bluetooth signals from Meta and Snap devices.

For (3), we relax our proposed test using techniques from robust statistics and imprecise probabilities.

Typically, deep RL algorithms learn a policy in an online trial-and-error fashion using millions to billions of data.

To address issues of group-level fairness in machine learning, it is natural to adjust model parameters based on specific fairness objectives over a sensitive-attributed validation set.

However, the exact formula for front-door adjustment depends on the structure of the graph, which is difficult to learn in practice.

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"