Rank Selection in Nonnegative Matrix Factorization using Minimum Description Length | Citedby Results | Neural Computation | MIT Press

Skip to Main Content

Skip Nav Destination

Rank Selection in Nonnegative Matrix Factorization using Minimum Description Length

Neural Computation (2017) 29 (8): 2164–2176.

This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.

Heterogeneity of technological structures between EU countries: An application of complex systems methods to Input–Output Tables

Andrea Mascaretti
Laura Dell’Agostino
Marika Arena
Andrea Flori
Alessandra Menafoglio
Simone Vantini

Expert Systems with Applications (2022) 206: 117875.

A network-based drug repurposing method via non-negative matrix factorization

Shaghayegh Sadeghi
Jianguo Lu
Alioune Ngom
Lenore Cowen

Bioinformatics (2022) 38 (5): 1369.

Tracking Proterozoic–Triassic sediment routing to western Laurentia via bivariate non-negative matrix factorization of detrital provenance data

Joel E. Saylor
Kurt E. Sundell

Journal of the Geological Society (2021) 178 (3)

Subgrouping by gene expression profiles to improve relapse risk prediction in paediatric B‐precursor acute lymphoblastic leukaemia

Qingsheng Huang
Jiayong Zhong
Huan Gao
Kuanrong Li
Huiying Liang

Cancer Medicine (2021) 10 (11): 3782.

Subject-specific EEG channel selection using non-negative matrix factorization for lower-limb motor imagery recognition

Dharmendra Gurve
Denis Delisle-Rodriguez
Maria Romero-Laiseca
Vivianne Cardoso
Flavia Loterio
Teodiano Bastos
Sri Krishnan

Journal of Neural Engineering (2020) 17 (2): 026029.

Leveraging maximum entropy and correlation on latent factors for learning representations

Zhicheng He
Jie Liu
Kai Dang
Fuzhen Zhuang
Yalou Huang

Neural Networks (2020) 131: 312.

A hybrid approach for stain normalisation in digital histopathological images

Faiza Bukenya

Multimedia Tools and Applications (2020) 79 (3-4): 2339.

Alternating Iteratively Reweighted Least Squares Minimization for Low-Rank Matrix Factorization

Paris V. Giampouras
Athanasios A. Rontogiannis
Konstantinos D. Koutroumbas

IEEE Transactions on Signal Processing (2019) 67 (2): 490.

Model Selection for Non-Negative Tensor Factorization with Minimum Description Length

Yunhui Fu
Shin Matsushima
Kenji Yamanishi

Entropy (2019) 21 (7): 632.