الملخص
The CANDECOMP/PARAFAC (CP) decomposition is widely used for revealing the underlying patterns from multiway data (also referred to as a higher-order tensor). When the data is clipped or saturated, however, the linear CP model becomes unreliable. Several remedies exist such as treating the clipped entries as missing or imputation; however, both fall short in different scenarios. We propose a nonlinear CP model (NCP) for pattern discovery in this setting, extending ideas from nonlinear matrix decompositions to tensors, and solve it using a flexible ADMM (Alternating Direction Method of Multipliers)-based framework that can accommodate a variety of nonlinearities. Using synthetic data with known factors and simulated metabolomics data where clipping arises from instrument detection limits, we demonstrate that NCP recovers the underlying factors more accurately than CP fitted to only the observed entries or threshold-imputed data.
الكلمات المفتاحية
الموضوع
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Awari, A., Ploeg, G. R. V. D., Vandaele, A., Gillis, N., & Acar, E. (2026). Nonlinear Tensor Decomposition for Pattern Discovery. https://omanscience.com/ar/articles/nonlinear-tensor-decomposition-for-pattern-discovery
MLA 9
Awari, Atharva, et al. "Nonlinear Tensor Decomposition for Pattern Discovery." https://omanscience.com/ar/articles/nonlinear-tensor-decomposition-for-pattern-discovery.
شيكاغو (المؤلف–التاريخ)
Awari, Atharva, Geert Roelof van der Ploeg, Arnaud Vandaele, Nicolas Gillis, and Evrim Acar. 2026. "Nonlinear Tensor Decomposition for Pattern Discovery." https://omanscience.com/ar/articles/nonlinear-tensor-decomposition-for-pattern-discovery.
هارفارد
Awari, A., Ploeg, G. R. V. D., Vandaele, A., Gillis, N. and Acar, E. (2026) 'Nonlinear Tensor Decomposition for Pattern Discovery', Available at: https://omanscience.com/ar/articles/nonlinear-tensor-decomposition-for-pattern-discovery.
فانكوفر
Awari A, Ploeg GRVD, Vandaele A, Gillis N, Acar E. Nonlinear Tensor Decomposition for Pattern Discovery. https://omanscience.com/ar/articles/nonlinear-tensor-decomposition-for-pattern-discovery
IEEE
A. Awari, G. R. V. D. Ploeg, A. Vandaele, N. Gillis, and E. Acar, "Nonlinear Tensor Decomposition for Pattern Discovery," https://omanscience.com/ar/articles/nonlinear-tensor-decomposition-for-pattern-discovery.