110 citations · 160 across the 15 of their papers we have counts for
8 papers · 1 filter
Nearly Optimal Bayesian Inference for Structural Missingness
Chen Liang, Donghua Yang, Yutong Zhao +9
Structural missingness breaks 'just impute and train': values can be undefined by causal or logical constraints, and the mask may depend on observed variables, unobserved variables…
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…
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…
UniTS: A Universal Time Series Analysis Framework Powered by Self-Supervised Representation Learning
Zhiyu Liang, Chen Liang, Zheng Liang +2
Machine learning has emerged as a powerful tool for time series analysis. Existing methods are usually customized for different analysis tasks and face challenges in tackling pract…
FedST: Secure Federated Shapelet Transformation for Time Series Classification
Zhiyu Liang, Hongzhi Wang
This paper explores how to build a shapelet-based time series classification (TSC) model in the federated learning (FL) scenario, that is, using more data from multiple owners with…