4 papers
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…
Robust Categorical Data Clustering Guided by Multi-Granular Competitive Learning
Shenghong Cai, Yiqun Zhang, Xiaopeng Luo +3
Data set composed of categorical features is very common in big data analysis tasks. Since categorical features are usually with a limited number of qualitative possible values, th…
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…
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…