3 citations · 3 across the 1 of their papers we have counts for
3 papers
A Parameter-free Adaptive Resonance Theory-based Topological Clustering Algorithm Capable of Continual Learning
Naoki Masuyama, Takanori Takebayashi, Yusuke Nojima +3
In general, a similarity threshold (i.e., a vigilance parameter) for a node learning process in Adaptive Resonance Theory (ART)-based algorithms has a significant impact on cluster…
An Adaptive Resonance Theory-based Topological Clustering Algorithm with a Self-Adjusting Vigilance Parameter
Naoki Masuyama, Yuichiro Toda, Yusuke Nojima +1
Clustering in stationary and nonstationary settings, where data distributions remain static or evolve over time, requires models that can adapt to distributional shifts while prese…
Integrating White and Black Box Techniques for Interpretable Machine Learning
Eric M. Vernon, Naoki Masuyama, Yusuke Nojima
In machine learning algorithm design, there exists a trade-off between the interpretability and performance of the algorithm. In general, algorithms which are simpler and easier fo…