A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted consumer data. By combining ...
Leaders across industries from airlines to packaged foods have said a growing divide between lower-income and wealthy consumers is changing their businesses. By Kailyn Rhone The U.S. economy is ...
Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
This project applies hierarchical clustering to group local authorities in England based on case closure reasons from the Children in Need Census (2013–2024). It supports benchmarking, policy ...
ABSTRACT: Doping is an issue associated with elite sports as athletes attempt to enhance their performance to gain an edge over other athletes. However, the prevalence of doping is continuously ...
Abstract: Traditional k-means clustering is widely used to analyze regional and temporal variations in time series data, such as sea levels. However, its accuracy can be affected by limitations, ...
Abstract: This paper introduces a codebook-based trellis-coded quantization (TCQ) approach utilizing K-means clustering, designed specifically for massive multiple-input multiple-output systems. The ...
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