Search Results for author: Chu Kiong Loo

Found 11 papers, 6 papers with code

Privacy-preserving Continual Federated Clustering via Adaptive Resonance Theory

1 code implementation7 Sep 2023 Naoki Masuyama, Yusuke Nojima, Yuichiro Toda, Chu Kiong Loo, Hisao Ishibuchi, Naoyuki Kubota

In the clustering domain, various algorithms with a federated learning framework (i. e., federated clustering) have been actively studied and showed high clustering performance while preserving data privacy.

Clustering Continual Learning +2

A Parameter-free Adaptive Resonance Theory-based Topological Clustering Algorithm Capable of Continual Learning

1 code implementation1 May 2023 Naoki Masuyama, Takanori Takebayashi, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi, Stefan Wermter

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 clustering performance.

Clustering Continual Learning

Modeling Generalized Specialist Approach To Train Quality Resilient Snapshot Ensemble

1 code implementation12 Jun 2022 Ghalib Ahmed Tahir, Chu Kiong Loo, Zongying Liu

During each training cycle of G-Specialist, a model is fine-tuned on the synthetic images generated by RQMixup, intermixing clean and distorted images of a particular distortion at a randomly chosen level.

Data Augmentation Transfer Learning

Lifelong Learning from Event-based Data

1 code implementation11 Nov 2021 Vadym Gryshchuk, Cornelius Weber, Chu Kiong Loo, Stefan Wermter

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 previously learned representations.

Multi-label Classification via Adaptive Resonance Theory-based Clustering

1 code implementation2 Mar 2021 Naoki Masuyama, Yusuke Nojima, Chu Kiong Loo, Hisao Ishibuchi

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 approach for label probability computation.

Classification Clustering +3

Explainable Goal-Driven Agents and Robots -- A Comprehensive Review

no code implementations21 Apr 2020 Fatai Sado, Chu Kiong Loo, Wei Shiung Liew, Matthias Kerzel, Stefan Wermter

The recent stance on the explainability of AI systems has witnessed several approaches on eXplainable Artificial Intelligence (XAI); however, most of the studies have focused on data-driven XAI systems applied in computational sciences.

Continual Learning Explainable artificial intelligence +2

Bio-Inspired Human Action Recognition using Hybrid Max-Product Neuro-Fuzzy Classifier and Quantum-Behaved PSO

no code implementations13 Sep 2015 Bardia Yousefi, Chu Kiong Loo

Studies on computational neuroscience through functional magnetic resonance imaging (fMRI) and following biological inspired system stated that human action recognition in the brain of mammalian leads two distinct pathways in the model, which are specialized for analysis of motion (optic flow) and form information.

Action Recognition Temporal Action Localization

Classify Images with Conceptor Network

no code implementations2 Jun 2015 Yuhuang Hu, M. S. Ishwarya, Chu Kiong Loo

This article demonstrates a new conceptor network based classifier in classifying images.

regression

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