Accurate PARAFAC2 Decomposition for Temporal Irregular Tensors with Missing Values

Author:

Jang Jun-Gi1,Lee Jeongyoung1,Park Jiwon1,Kang U1

Affiliation:

1. Seoul National University,Seoul,Republic of Korea

Publisher

IEEE

Reference35 articles.

1. SliceNStitch: Continuous CP Decomposition of Sparse Tensor Streams

2. TedPar: Temporally Dependent PARAFAC2 Factorization for Phenotype-based Disease Progression Modeling

3. A Tensor Decomposition-Based Anomaly Detection Algorithm for Hyperspectral Image

4. Taste: Temporal and static tensor factorization for phenotyping electronic health records;afshar;Children,2020

5. Tensor decompositions for temporal knowledge base completion;lacroix;ICLRE,2020

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1. Fast and Accurate Domain Adaptation for Irregular Tensor Decomposition;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. Region of interest selection for GC×GC–MS data using a pseudo fisher ratio moving window with connected components segmentation;Journal of Chromatography Open;2023-11

3. Fast and Accurate Dual-Way Streaming PARAFAC2 for Irregular Tensors - Algorithm and Application;Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2023-08-04

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