Neuromorphic computers modeled after the human brain can now solve the complex equations behind physics simulations — something once thought possible only with energy-hungry supercomputers. The ...
Abstract: Identifying positive influence dominating set (PIDS) with the smallest cardinality can produce positive effect with the minimal cost on a social network. The purpose of this article is to ...
Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...
The team used an AI method known as equation discovery to develop a model to simulate the interactions between small eddies—circular, vortex-like currents—and large-scale ones. These interactions are ...
RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.
Estimating the number of triangles in a graph is a fundamental problem and has found applications in many fields. This ...
Medical device makers have been rushing to add AI to their products. While proponents say the new technology will revolutionize medicine, regulators are receiving a rising number of claims of patient ...
I ran mental health for Indiana. Banning kids from social media lets us avoid the harder question: Why can't we control ourselves?
Gift from Thomas and Susan Dunn supports creation of the Bike Shop @UChicago, which aims to shape AI development and build ...
Abstract: This article proposes a distributed time-varying optimization approach to address the dynamic resource allocation problem, leveraging a sliding mode technique. The algorithm integrates a ...
An executive came for a career talk and few students showed up. That's not apathy. It's a probability problem — and it's ...
Machine learning systems embed preferences either in training losses or through post-processing of calibrated predictions. Applying information design methods from Strack and Yang (2024), this paper ...
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