3 papers
cs.LG2025
Class Incremental Fault Diagnosis under Limited Fault Data via Supervised Contrastive Knowledge Distillation
Hanrong Zhang, Yifei Yao, Zixuan Wang +4
Class-incremental fault diagnosis requires a model to adapt to new fault classes while retaining previous knowledge. However, limited research exists for imbalanced and long-tailed…
cs.LG2024
TSINR: Capturing Temporal Continuity via Implicit Neural Representations for Time Series Anomaly Detection
Mengxuan Li, Ke Liu, Hongyang Chen +3
Time series anomaly detection aims to identify unusual patterns in data or deviations from systems' expected behavior. The reconstruction-based methods are the mainstream in this t…
cs.LG2022
Supervised Contrastive Learning with Tree-Structured Parzen Estimator Bayesian Optimization for Imbalanced Tabular Data
Shuting Tao, Peng Peng, Qi Li +1
Class imbalance has a detrimental effect on the predictive performance of most supervised learning algorithms as the imbalanced distribution can lead to a bias preferring the major…