78 citations · 81 across the 7 of their papers we have counts for
9 papers · 1 filter
Seeing Time: Visual-Temporal Representation Learning for Interpretable Time Series Clustering
Zheng Zhu, Zexi Tan, Yuming Deng +1
Multivariate Time Series (MTS) clustering is an important tool in temporal data mining, aiming to discover latent group structures from complex observations without supervision. Al…
AnchorMoE: Interpretable Time Series Classification via Anchor-Routed MoE
Tao Xie, Zexi Tan, Haoyi Xiao +5
Multivariate time series classification (MTSC) is pivotal in high-stakes domains, such as clinical diagnosis and industrial fault detection, where safe deployment necessitates tran…
Hierarchical Reference Sets for Robust Unsupervised Detection of Scattered and Clustered Outliers
Yiqun Zhang, Zexi Tan, Xiaopeng Luo +1
Most real-world IoT data analysis tasks, such as clustering and anomaly event detection, are unsupervised and highly susceptible to the presence of outliers. In addition to sporadi…
TFEC: Multivariate Time-Series Clustering via Temporal-Frequency Enhanced Contrastive Learning
Zexi Tan, Tao Xie, Haoyi Xiao +5
Multivariate Time-Series (MTS) clustering is crucial for signal processing and data analysis. Although deep learning approaches, particularly those leveraging Contrastive Learning…
HMVI: Unifying Heterogeneous Attributes with Natural Neighbors for Missing Value Inference
Xiaopeng Luo, Zexi Tan, Zhuowei Wang
Missing value imputation is a fundamental challenge in machine intelligence, heavily dependent on data completeness. Current imputation methods often handle numerical and categoric…
Mask the Redundancy: Evolving Masking Representation Learning for Multivariate Time-Series Clustering
Zexi Tan, Xiaopeng Luo, Yunlin Liu +1
Multivariate Time-Series (MTS) clustering discovers intrinsic grouping patterns of temporal data samples. Although time-series provide rich discriminative information, they also co…
DE3S: Dual-Enhanced Soft-Sparse-Shape Learning for Medical Early Time-Series Classification
Tao Xie, Zexi Tan, Haoyi Xiao +2
Early Time Series Classification (ETSC) is critical in time-sensitive medical applications such as sepsis, yet it presents an inherent trade-off between accuracy and earliness. Thi…
MEET-Sepsis: Multi-Endogenous-View Enhanced Time-Series Representation Learning for Early Sepsis Prediction
Zexi Tan, Tao Xie, Binbin Sun +3
Sepsis is a life-threatening infectious syndrome associated with high mortality in intensive care units (ICUs). Early and accurate sepsis prediction (SP) is critical for timely int…
Learning Self-Growth Maps for Fast and Accurate Imbalanced Streaming Data Clustering
Yiqun Zhang, Sen Feng, Pengkai Wang +5
Streaming data clustering is a popular research topic in data mining and machine learning. Since streaming data is usually analyzed in data chunks, it is more susceptible to encoun…