14 citations
- Brookhaven National LaboratoryUS1 paper
- California Institute of TechnologyUS1 paper
- Carnegie Mellon UniversityUS1 paper
- Central China Normal UniversityCN1 paper
- Chennai Mathematical InstituteIN1 paper
- East Carolina UniversityUS1 paper
- Infrared Processing and Analysis CenterUS1 paper
- Lawrence Berkeley National LaboratoryUS1 paper
- Neural Analytics (United States)US1 paper
- Systems Analytics (United States)US1 paper
- Teledyne Technologies (United States)US1 paper
- Tuskegee UniversityUS1 paper
7 papers
Decreasing Digital Distraction in College Students: Associated Online Learning Strategies Identified by Unsupervised Data Mining Approaches
Hui Shi, Ran Bi, Xi Lin +1
The proliferation of digital tools in education offers numerous benefits but also introduces significant challenges, notably digital distractions that hinder academic performance,…
Empirically-Calibrated H100 Node Power Models for Reducing Uncertainty in AI Training Energy Estimation
Alex C. Newkirk, Jared Fernandez, Jonathan Koomey +4
As AI's energy demand continues to grow, it is critical to enhance the understanding of characteristics of this demand, to improve grid infrastructure planning and environmental as…
Direct-to-Cell: A First Look into Starlink's Direct Satellite-to-Device Radio Access Network through Crowdsourced Measurements
Jorge Garcia-Cabeza, Javier Albert-Smet, Zoraida Frias +3
Low Earth Orbit (LEO) satellite mega-constellations have emerged as a viable access solution for broadband connectivity in underserved areas. In 2024, Starlink, in partnership with…
Evaluating the GeoSnap 13-m Cut-Off HgCdTe Detector for mid-IR ground-based astronomy
Jarron M. Leisenring, Dani Atkinson, Rory Bowens +13
New mid-infrared HgCdTe (MCT) detector arrays developed in collaboration with Teledyne Imaging Sensors (TIS) have paved the way for improved 10-m sensors for space- and ground-b…
Weakly-Convex Concave Min-Max Optimization: Provable Algorithms and Applications in Machine Learning
Hassan Rafique, Mingrui Liu, Qihang Lin +1
Min-max problems have broad applications in machine learning, including learning with non-decomposable loss and learning with robustness to data distribution. Convex-concave min-ma…
Measuring Economic Resilience to Natural Disasters with Big Economic Transaction Data
Elena Alfaro Martinez, Maria Hernandez Rubio, Roberto Maestre Martinez +5
This research explores the potential to analyze bank card payments and ATM cash withdrawals in order to map and quantify how people are impacted by and recover from natural disaste…