activity
20242026
most citedLearning Self-Growth Maps for Fast and Accurate Imbalanced Streaming Data Clustering

78 citations · 81 across the 7 of their papers we have counts for

collaborators
Showing 2026Show all

5 papers · 1 filter

cs.LG2026

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…

cs.LG2026

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…

cs.LG2026★ 2 cited

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…

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…