2 citations · 7 across the 17 of their papers we have counts for
5 papers · 1 filter
Awesome-OL: An Extensible Toolkit for Online Learning
Zeyi Liu, Songqiao Hu, Pengyu Han +2
In recent years, online learning has attracted increasing attention due to its adaptive capability to process streaming and non-stationary data. To facilitate algorithm development…
Lite-RVFL: A Lightweight Random Vector Functional-Link Neural Network for Learning Under Concept Drift
Songqiao Hu, Zeyi Liu, Xiao He
The change in data distribution over time, also known as concept drift, poses a significant challenge to the reliability of online learning methods. Existing methods typically requ…
PB-OEL: A Performance-Bounded Online Ensemble Learning Framework With Mixed Feedback for Real-Time Safety Assessment
Songqiao Hu, Zeyi Liu, Lufeng Hao +2
Real-time safety assessment is critical for ensuring the reliable operation of complex dynamic systems. However, obtaining full safety labels in real time is often prohibitively ex…
An Evidential Real-Time Multi-Mode Fault Diagnosis Approach Based on Broad Learning System
Chen Li, Zeyi Liu, Limin Wang +2
Fault diagnosis is a crucial area of research in industry. Industrial processes exhibit diverse operating conditions, where data often have non-Gaussian, multi-mode, and center-dri…
CADM: Confusion Model-based Detection Method for Real-drift in Chunk Data Stream
Songqiao Hu, Zeyi Liu, Xiao He
Concept drift detection has attracted considerable attention due to its importance in many real-world applications such as health monitoring and fault diagnosis. Conventionally, mo…