학술논문
Coupled Tensor Factorization for Flow Cytometry Data Analysis
Document Type
Conference
Author
Source
2022 IEEE 32nd International Workshop on Machine Learning for Signal Processing (MLSP) Machine Learning for Signal Processing (MLSP), 2022 IEEE 32nd International Workshop on. :1-6 Aug, 2022
Subject
Language
ISSN
2161-0371
Abstract
In this paper, we propose a new method for automated flow cytometry data analysis. By modeling a multidimensional probability distribution as a mixture of simpler distributions, we can reformulate the problem as a coupled tensor approximation of 3D marginals. In order to reduce the computational load, we use partially coupled strategies. We also propose a grouping of rank-one components together with a new visualization of the results. We demonstrate the usefulness of the proposed methodology on simulated and real data.