Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
A first-of-its-kind national trial shows that public Montessori preschool students enter kindergarten with stronger reading, ...
Abstract: The major challenge in learning-based RF sensing is acquiring high-quality large-scale annotated datasets. Unlike visual datasets, RF signals are inherently non-intuitive and ...
Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...
Abstract: Unsupervised learning methods effectively reduce the noise level of positron emission tomography (PET) images with limited training data. Recent research indicates that the performance of ...
Unleashing a more efficient approach to fine-tuning reasoning in large language models, recent work by researchers at Tencent AI Lab and The Chinese University of Hong Kong introduces Unsupervised ...
Researchers have introduced Torque Clustering, an AI algorithm that enhances unsupervised learning by mimicking natural intelligence. Unlike traditional supervised methods, it identifies patterns ...
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