In this paper, we study a graph pattern matching problem, which is to find all patterns in a large data graph that match a user-given graph pattern. We propose new two-step R-join (reachability join) ...

The HGN is an improvement on the already published original graph neuron (GN) algorithm. In this improved approach, it recognizes incomplete/noisy patterns. It also resolves the crosstalk problem, ...

This is the first book to explore GMDH using MATLAB (matrix laboratory) language. Readers will learn how to implement GMDH in MATLAB as a method of dealing with big data analytics. Error-free source ...

Machine Learning course from Stanford University on Coursera. We will implement an anomaly detection algorithm to detect anomalous behavior in server computers. The features measure the through put ...

This repository contains the Code of the model in the ICML’25 paper "Non-Stationary Predictions May Be More Informative: Exploring Pseudo-Labels with a Two-Phase Pattern of Training ... code is ...

One of the most advanced fields of science is “graph theory,” which plays a vital role in the applications of other branches of science like chemistry, biology, physics, electrical engineering, ...

World Population Prospects 2022 is the twenty-seventh edition of the official United Nations population estimates and projections.It presents population estimates from 1950 to the present for 237 ...

The data points per indicator and class should not be interpreted in isolation; instead, the different graph patterns can be compared. Figure 4. Average response values per indicator variable per ...