230 citations · 392 across the 8 of their papers we have counts for
6 papers · 1 filter
An Integrated Fusion Framework for Ensemble Learning Leveraging Gradient Boosting and Fuzzy Rule-Based Models
Jinbo Li, Peng Liu, Long Chen +2
The integration of different learning paradigms has long been a focus of machine learning research, aimed at overcoming the inherent limitations of individual methods. Fuzzy rule-b…
Clustering-based Anomaly Detection in Multivariate Time Series Data
Jinbo Li, Hesam Izakian, Witold Pedrycz +1
Multivariate time series data come as a collection of time series describing different aspects of a certain temporal phenomenon. Anomaly detection in this type of data constitutes…
Multivariate Time series Anomaly Detection:A Framework of Hidden Markov Models
Jinbo Li, Witold Pedrycz, Iqbal Jamal
In this study, we develop an approach to multivariate time series anomaly detection focused on the transformation of multivariate time series to univariate time series. Several tra…
BRAINCELL-AID: An Agentic AI Created Brain Cell Type Resource for Community Annotation
Rongbin Li, Wenbo Chen, Zhao Li +13
Single-cell RNA sequencing has transformed our ability to identify diverse cell types and their transcriptomic signatures. However, annotating these signatures-especially those inv…
AXIS: Explainable Time Series Anomaly Detection with Large Language Models
Tian Lan, Hao Duong Le, Jinbo Li +4
Time-series anomaly detection (TSAD) increasingly demands explanations that articulate not only if an anomaly occurred, but also what pattern it exhibits and why it is anomalous. L…
Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy
Tian Lan, Hao Duong Le, Jinbo Li +4
Time series anomaly detection (TSAD) is a critical task, but developing models that generalize to unseen data in a zero-shot manner remains challenging. Existing foundation models…