316 citations · 992 across the 28 of their papers we have counts for
9 papers · 1 filter
PHIDA: Persistence-Guided Node-to-Cluster Mapping for Online Clustering
Naoki Masuyama, Yusuke Nojima, Stefan Wermter +3
Online clustering methods that adaptively create and update nodes as data arrive often make node learning explicit, whereas the mapping from the learned node state to output cluste…
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…
Adapting Rule Representation With Four-Parameter Beta Distribution for Learning Classifier Systems
Hiroki Shiraishi, Yohei Hayamizu, Tomonori Hashiyama +3
Rule representations significantly influence the search capabilities and decision boundaries within the search space of Learning Classifier Systems (LCSs), a family of rule-based m…
A Class Inference Scheme With Dempster-Shafer Theory for Learning Fuzzy-Classifier Systems
Hiroki Shiraishi, Hisao Ishibuchi, Masaya Nakata
The decision-making process significantly influences the predictions of machine learning models. This is especially important in rule-based systems such as Learning Fuzzy-Classifie…
X-KAN: Optimizing Local Kolmogorov-Arnold Networks via Evolutionary Rule-Based Machine Learning
Hiroki Shiraishi, Hisao Ishibuchi, Masaya Nakata
Function approximation is a critical task in various fields. However, existing neural network approaches struggle with locally complex or discontinuous functions due to their relia…
Pareto Front Shape-Agnostic Pareto Set Learning in Multi-Objective Optimization
Rongguang Ye, Longcan Chen, Wei-Bin Kou +2
Pareto set learning (PSL) is an emerging approach for acquiring the complete Pareto set of a multi-objective optimization problem. Existing methods primarily rely on the mapping of…