26 citations · 56 across the 15 of their papers we have counts for
5 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…
Privacy-preserving Continual Federated Clustering via Adaptive Resonance Theory
Naoki Masuyama, Yusuke Nojima, Yuichiro Toda +3
With the increasing importance of data privacy protection, various privacy-preserving machine learning methods have been proposed. In the clustering domain, various algorithms with…
Explainable Lifelong Stream Learning Based on "Glocal" Pairwise Fusion
Chu Kiong Loo, Wei Shiung Liew, Stefan Wermter
Real-time on-device continual learning applications are used on mobile phones, consumer robots, and smart appliances. Such devices have limited processing and memory storage capabi…
Lifelong Learning from Event-based Data
Vadym Gryshchuk, Cornelius Weber, Chu Kiong Loo +1
Lifelong learning is a long-standing aim for artificial agents that act in dynamic environments, in which an agent needs to accumulate knowledge incrementally without forgetting pr…
Multi-label Classification via Adaptive Resonance Theory-based Clustering
Naoki Masuyama, Yusuke Nojima, Chu Kiong Loo +1
This paper proposes a multi-label classification algorithm capable of continual learning by applying an Adaptive Resonance Theory (ART)-based clustering algorithm and the Bayesian…