Abstract: K-means is one of the most simple and popular clustering algorithms, which implemented as a standard clustering method in most of machine learning researches. The goal of K-means clustering ...

Abstract: Energy load balancing is an essential issue in designing wireless sensor networks (WSNs). Clustering techniques are utilized as energy-efficient methods to balance the network energy and ...

About This project uses K-Means Clustering, an unsupervised machine learning algorithm, to perform customer segmentation based on various attributes such as spending habits, purchasing frequency, and ...

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

📄 CV Parsing - Extract skills from PDF documents 🧠 ML Clustering - K-Means, Hierarchical, and DBSCAN clustering 🎯 Career Clusters - 10 career categories with detailed insights 📚 Learning Resources ...

Tonight, as you drift toward sleep, your mind may begin to dream before your brain has officially crossed into sleep. You may ...

We study the problem of privacy-preserving k-means clustering in the horizontally federated setting. Existing federated approaches using secure computation suffer from substantial overheads and do not ...

Objective SLE is a heterogeneous systemic autoimmune disease with diverse clinical manifestations. We aimed to identify ...

Cell death in dementia has long posed a frustrating problem. Toxic proteins pile up inside neurons in Alzheimer’s disease and ...

What about ChatGPT and related large AI Systems? How will they impact us all? As a longtime researcher in AI, I'm excited about the ways in which these new AI systems can improve our healthcare, ...