Co-clustering: a Survey of the Main Methods, Recent Trends and Open Problems
E Battaglia, F Peiretti, RG Pensa - ACM Computing Surveys, 2024 - dl.acm.org
Since its early formulations, co-clustering has gained popularity and interest both within and
outside the machine learning community as a powerful learning paradigm for clustering high …
outside the machine learning community as a powerful learning paradigm for clustering high …
Detecting of Robotic Imitation of Human on-the-Website Activity with Advanced Vector Analysis and Fractional Derivatives
IP Malashin, VS Tynchenko, AP Gantimurov… - IEEE …, 2024 - ieeexplore.ieee.org
This paper introduces a novel approach for the detection of automated entities in online
environments through the analysis of mouse dynamics. Leveraging fractional derivatives …
environments through the analysis of mouse dynamics. Leveraging fractional derivatives …
On the Attractive and Repulsive Forces of Generalized Stochastic Neighbor Embedding With Alpha-Divergence
Stochastic neighbor embedding (SNE) performs nonlinear transformation from high-
dimensional observation space to low-dimensional latent space which preserves neighbor …
dimensional observation space to low-dimensional latent space which preserves neighbor …
[PDF][PDF] MATHEMATICAL METHODS OF MULTIDIMENSIONAL DATA INTELLIGENT ANALYSIS
V Ismailov, K Yalova - AGRICULTURAL SCIENCES, 2024 - nor-ijournal.com
The presented article is of an overview nature, the purpose of which is to describe the main
methods that can be used to analyze and visualize the multidimensional and big data …
methods that can be used to analyze and visualize the multidimensional and big data …