most citedMask the Redundancy: Evolving Masking Representation Learning for Multivariate Time-Series Clustering

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2026

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…

cs.LG2026

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…

cs.LG20251 cited

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…

cs.LG2025

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…

cs.LG2025

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…