Towards Long-term Annotators: A Supervised Label Aggregation Baseline

no code implementations • 15 Nov 2023 • Haoyu Liu, Fei Wang, Minmin Lin, Runze Wu, Renyu Zhu, Shiwei Zhao, Kai Wang, Tangjie Lv, Changjie Fan

These annotators could leave substantial historical annotation records on the crowdsourcing platforms, which can benefit label aggregation, but are ignored by previous works.

Examining the Effect of Pre-training on Time Series Classification

no code implementations • 11 Sep 2023 • Jiashu Pu, Shiwei Zhao, Ling Cheng, Yongzhu Chang, Runze Wu, Tangjie Lv, Rongsheng Zhang

(iv) Adding more pre-training data does not improve generalization, but it can strengthen the advantage of pre-training on the original data volume, such as faster convergence.

Time Series Time Series Classification +1

Omni-frequency Channel-selection Representations for Unsupervised Anomaly Detection

1 code implementation • 1 Mar 2022 • Yufei Liang, Jiangning Zhang, Shiwei Zhao, Runze Wu, Yong liu, Shuwen Pan

Density-based and classification-based methods have ruled unsupervised anomaly detection in recent years, while reconstruction-based methods are rarely mentioned for the poor reconstruction ability and low performance.

Unsupervised Anomaly Detection