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Found 4 papers, 0 papers with code
Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling
Moreover, a case study in the station clustering based on real passenger flow data is conducted, with quite valuable insights discovered.
Personalized Tucker Decomposition: Modeling Commonality and Peculiarity on Tensor Data
We propose personalized Tucker decomposition (perTucker) to address the limitations of traditional tensor decomposition methods in capturing heterogeneity across different datasets.
Adaptive Resources Allocation CUSUM for Binomial Count Data Monitoring with Application to COVID-19 Hotspot Detection
In this paper, we present an efficient statistical method (denoted as "Adaptive Resources Allocation CUSUM") to robustly and efficiently detect the hotspot with limited sampling resources.
Adaptive Partially-Observed Sequential Change Detection and Isolation
High-dimensional data has become popular due to the easy accessibility of sensors in modern industrial applications.
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