A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted consumer data. By combining secure clustering with efficient computation, the study ...

Kiev outpaces Russia in the technological race. Its advancements allow it to train AI drones and spy on Moscow with real-time ...

According to Fidelity, the total 401 (k) savings rate — which includes both employer and employee contributions — reached an all-time high of 14.4% in the first quarter. That means 401 (k) savers are ...

Algorithms are everywhere, even when we do not notice them. They help us search the web, navigate roads, and discover new content online. Understanding how algorithms work is one of the simplest ways ...

Abstract: The K-means algorithm is a partition-based clustering approach with two notable drawbacks, sensitivity to the initial center and a tendency to converge to suboptimal solutions. To address ...

Unsupervised learning is a branch of machine learning that focuses on analyzing unlabeled data to uncover hidden patterns, structures, and relationships. Unlike supervised learning, which requires pre ...

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, ...

Abstract: For radar signal sorting based on pulse descriptors, the inherent limitations of the traditional K-means algorithm include the requirement of a predefined number of clusters, the sensitivity ...

Cryptography secures communication in banking, messaging, and blockchain. Good algorithms (AES, RSA, ECC, SHA-2/3, ChaCha20) are secure, efficient, and widely trusted. Bad algorithms (DES, MD5, SHA-1, ...

Amsterdam’s struggles with its welfare fraud algorithm show us the stakes of deploying AI in situations that directly affect human lives. What Amsterdam’s welfare fraud algorithm taught me about fair ...