This article studies the problem of computing zero-forcing sets (ZFS) in graphs and provides a machine-learning solution. Zero-forcing is a vertex coloring process to color the entire vertex set from ...

Machine learning is widely used in various applications such as data mining, computer vision, and bioinformatics owing to the explosion of available data. However, in practice, many data have some ...

Most machine learning algorithms demand a huge number of matrix multiplications and other mathematical operations ... The far-right side of the graph in Figure 11 shows a pattern of overfitting ...

First is Node2Vec, a popular graph embedding algorithm that uses neural networks to learn continuous feature representations for nodes, which can then be used for downstream machine learning tasks.

This article explores what knowledge graphs are, why they are becoming a favourable data storage format, and discusses their potential to improve artificial intelligence and machine learning ...

During his studies, he developed a solid background in several areas, including algorithm design, graph theory, and machine learning. In January 2020, he received his joint Ph.D. from the University ...

We use machine learning and graph algorithms to analyze the attributes of TRON addresses with the goal of assisting in the tracking of illicit funds. misttrack.io. Topics. machine-learning ...

New machine learning algorithm promises advances in computing. ScienceDaily. Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2024 / 05 / 240509155536.htm. Ohio State University.

Tohoku University. (2024, December 10). New algorithm boosts multitasking in quantum machine learning. ScienceDaily. Retrieved June 11, 2025 from www.sciencedaily.com / releases / 2024 / 12 ...