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Adaptive Resonance Theory-based Topological Clustering with a Divisive
  Hierarchical Structure Capable of Continual Learning
v1v2v3v4 (latest)

Adaptive Resonance Theory-based Topological Clustering with a Divisive Hierarchical Structure Capable of Continual Learning

26 January 2022
Naoki Masuyama
Narito Amako
Yuna Yamada
Yusuke Nojima
H. Ishibuchi
ArXiv (abs)PDFHTML

Papers citing "Adaptive Resonance Theory-based Topological Clustering with a Divisive Hierarchical Structure Capable of Continual Learning"

2 / 2 papers shown
Title
Privacy-preserving Continual Federated Clustering via Adaptive Resonance
  Theory
Privacy-preserving Continual Federated Clustering via Adaptive Resonance Theory
Naoki Masuyama
Yusuke Nojima
Y. Toda
C. K. Loo
H. Ishibuchi
N. Kubota
FedML
75
3
0
07 Sep 2023
Reference Vector Adaptation and Mating Selection Strategy via Adaptive
  Resonance Theory-based Clustering for Many-objective Optimization
Reference Vector Adaptation and Mating Selection Strategy via Adaptive Resonance Theory-based Clustering for Many-objective Optimization
Takato Kinoshita
Naoki Masuyama
Yiping Liu
Yusuke Nojima
H. Ishibuchi
20
3
0
22 Apr 2022
1