Privacy-preserving computer vision is an important emerg- ing problem in machine learning and artificial intelligence. The prevalent methods tackling this problem use differential privacy or anonymization and obfuscation techniques to protect the privacy of individuals. In b…

In this paper, we propose WaterMark Detection (WMD), the first invisible watermark detection method under a black-box and annotation-free setting. WMD is capable of detecting arbitrary watermarks within a given reference dataset using a clean non watermarked dataset as a ref…

An open problem in differentially private deep learning is hyperparameter optimization (HPO). DP-SGD introduces new hyperparameters and complicates existing ones, forcing researchers to painstakingly tune hyperparameters with hundreds of trials, which in turn makes it imposs…