6 papers
KDSelector: A Knowledge-Enhanced and Data-Efficient Model Selector Learning Framework for Time Series Anomaly Detection
Zhiyu Liang, Dongrui Cai, Chenyuan Zhang +6
Model selection has been raised as an essential problem in the area of time series anomaly detection (TSAD), because there is no single best TSAD model for the highly heterogeneous…
An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut Problem
Huaiyuan Liu, Xianzhang Liu, Donghua Yang +5
The Maximum Minimal Cut Problem (MMCP), a NP-hard combinatorial optimization (CO) problem, has not received much attention due to the demanding and challenging bi-connectivity cons…
TimeCSL: Unsupervised Contrastive Learning of General Shapelets for Explorable Time Series Analysis
Zhiyu Liang, Chen Liang, Zheng Liang +2
Unsupervised (a.k.a. Self-supervised) representation learning (URL) has emerged as a new paradigm for time series analysis, because it has the ability to learn generalizable time s…
Unsupervised Multi-modal Feature Alignment for Time Series Representation Learning
Chen Liang, Donghua Yang, Zhiyu Liang +4
In recent times, the field of unsupervised representation learning (URL) for time series data has garnered significant interest due to its remarkable adaptability across diverse do…
A Shapelet-based Framework for Unsupervised Multivariate Time Series Representation Learning
Zhiyu Liang, Jianfeng Zhang, Chen Liang +3
Recent studies have shown great promise in unsupervised representation learning (URL) for multivariate time series, because URL has the capability in learning generalizable represe…
TodyNet: Temporal Dynamic Graph Neural Network for Multivariate Time Series Classification
Huaiyuan Liu, Xianzhang Liu, Donghua Yang +4
Multivariate time series classification (MTSC) is an important data mining task, which can be effectively solved by popular deep learning technology. Unfortunately, the existing de…