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cs.LG2024
Clustering in Dynamic Environments: A Framework for Benchmark Dataset Generation With Heterogeneous Changes
Danial Yazdani, Juergen Branke, Mohammad Sadegh Khorshidi +4
Clustering in dynamic environments is of increasing importance, with broad applications ranging from real-time data analysis and online unsupervised learning to dynamic facility lo…
cs.LG2024
Semantic-Preserving Feature Partitioning for Multi-View Ensemble Learning
Mohammad Sadegh Khorshidi, Navid Yazdanjue, Hassan Gharoun +4
In machine learning, the exponential growth of data and the associated ``curse of dimensionality'' pose significant challenges, particularly with expansive yet sparse datasets. Add…