Visual Studio Magazine

Data Clustering Using Entropy Minimization

Entropy Minimization is a new clustering algorithm that works with both categorical and numeric data, and scales well to extremely large data sets. Data clustering is the process of placing data items ...
JSTOR Daily

Clustering Huge Number of Financial Time Series: A Panel Data Approach With High-Dimensional Predictors and Factor Structures

This article Introduces a new procedure for clustering a large number of financial time series based on high-dimensional panel data with grouped factor structures. The proposed method attempts to ...
Visual Studio Magazine

DBSCAN Data Clustering from Scratch Using C#

Compared to other clustering techniques, DBSCAN does not require you to explicitly specify how many data clusters to use, explains Dr. James McCaffrey of Microsoft Research in this full-code, ...
manilatimes

WiMi Launches Quantum-Assisted Unsupervised Data Clustering Technology Based on Neural Networks

BEIJING, Oct. 1, 2025 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced the ...
Network World

Virtualization and clustering: combining two winning strategies

Virtualization and clustering can be two faces of the same coin. Computing virtualization is a very hot topic for data center managers. Whether the motivation is higher utilization, reduced management ...
JSTOR Daily

Cluster–Robust Variance Estimation for Dyadic Data

Dyadic data are common in the social sciences, although inference for such settings involves accounting for a complex clustering structure. Many analyses in the social sciences fail to account for the ...

Potentially distinct structure in Kuiper belt discovered with help of clustering algorithm

A vast region of our solar system, called the Kuiper belt, stretches from the orbit of Neptune out to 50 or so astronomical ...