Wepropose twoinnovativealgorithms, DP-GLMtron and DP-TAGLMtron, that outperform the conventional DPSGD. Inlight ofthevast quantities of personal and sensitiveinformation involved, traditional methods of ensuring privacy are encountering significant challenges.

We introduce and study Swap Agnostic Learning.

In addition, we introduce a simple baseline, "RDumb", that periodically resets the

Unmanned Aerial V ehicles (UA Vs), equipped with cameras, are employed in numerous applications, including aerial photography, surveillance, and agriculture. In these applications, robust object detection and tracking are essential for the effective deployment of UA Vs.

Why are experts sounding the alarm on AI risks? In recent months, artificial intelligence has been in the news for the wrong reasons: use of deepfakes to scam people, AI systems used to manipulate cyberattacks, and chatbots encouraging suicides, among others. Experts are already warning against technology going out of control. Researchers with some of the most prominent AI companies have quit their jobs in recent weeks and publicly sounded the alarm about fast-paced technological development posing risks to society. But the recent slew of public resignations by those tasked with ensuring AI remains safe for humanity is making conversations around how to regulate the technology and slow its development more urgent, even as billions are being generated in AI investments.

Despite the success of DPM in practice, the mechanism behind it remains to be explored.