Abstract: The low detectability and low cost of uncrewed aerial vehicles (UAVs) allow them to swarm near the radar network for effective jamming. The key to jamming is the reasonable task assignment ...

Abstract: Quantitative risk allocation methods have attractive features, such as robust risk exposition and risk allocation control, which tend to affect their out-of-sample returns. Besides, recent ...

A view of an IRS Direct File promotional sign at the Internal Revenue Service Building on April 5, 2024 in Washington, D.C. (Photo by Tasos Katopodis/Getty Images for Economic Security Project) The ...

The Internal Revenue Service vastly overstated the projected costs of operating the Direct File free tax preparation program before terminating it for this tax season, according to a new report.

LOS ANGELES—There's been a flurry of recent activity in the direct-to-consumer space as drug costs and spending continue to rise. It's with that backdrop that GoodRx announced Tuesday it would launch ...

Multi-agent task allocation plays a crucial role in achieving efficient collaboration in heterogeneous multi-agent systems, especially in complex and dynamic environments. However, existing ...

Researchers at Nvidia have developed a technique that can reduce the memory costs of large language model reasoning by up to eight times. Their technique, called dynamic memory sparsification (DMS), ...

LISBON, Feb 5 (Reuters) - Portugal faces more than 4 billion euros ($4.7 billion) in direct reconstruction costs following last week’s devastating Storm Kristin, Economy Minister Manuel Castro Almeida ...

The Department of Health and Human Services issued a special advisory bulletin clarifying that pharmaceutical manufacturers may sell lower-cost prescription drugs directly to Medicare and Medicaid ...

Can drugmakers find a way around the pharmacy benefit manager model often blamed for rising drug costs? Some pharma companies are giving it a shot by reaching out directly to large, self-insured ...

A new study from researchers at Stanford University and Nvidia proposes a way for AI models to keep learning after deployment — without increasing inference costs. For enterprise agents that have to ...