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Found 3 papers, 1 papers with code
A Comprehensive Review of Community Detection in Graphs
This review article delves into the topic of community detection in graphs, which serves as a thorough exposition of various community detection methods from perspectives of modularity-based method, spectral clustering, probabilistic modelling, and deep learning.
Community Detection Using Revised Medoid-Shift Based on KNN
During the process of finding the next medoid, the RMS algorithm is based on a neighborhood defined by KNN, while the original Medoid-Shift is based on a neighborhood defined by a distance parameter.
Balanced Multimodal Learning via On-the-fly Gradient Modulation
Multimodal learning helps to comprehensively understand the world, by integrating different senses.
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