Another Robust NMF: Rethinking the Hyperbolic Tangent Function and Locality Constraint
IEEE Access, 2019 Non-negative matrix factorization (NMF) is a classical data analysis tool for clustering tasks. It usually considers the squared loss to measure the reconstruction error, thus it is sensitive to the presence of outliers. Looking into the literature, most
Xingyu Shen +4 more
doaj +2 more sources
A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts
Frontiers in Sociology, 2022 The richness of social media data has opened a new avenue for social science research to gain insights into human behaviors and experiences. In particular, emerging data-driven approaches relying on topic models provide entirely new perspectives on ...
R. Egger, Joanne Yu
semanticscholar +1 more source
Weighted Residual NMF With Spatial Regularization for Hyperspectral Unmixing
IEEE Geoscience and Remote Sensing Letters, 2022 This letter proposes a weighted residual nonnegative matrix factorization (NMF) with spatial regularization to unmix hyperspectral (HS) data. NMF decomposes a matrix into the product of two nonnegative matrices.
Taner Ince, N. Dobigeon
semanticscholar +1 more source
Global-Local Enhancement Network for NMF-Aware Sign Language Recognition [PDF]
ACM Trans. Multim. Comput. Commun. Appl., 2020 Sign language recognition (SLR) is a challenging problem, involving complex manual features (i.e., hand gestures) and fine-grained non-manual features (NMFs) (i.e., facial expression, mouth shapes, etc.). Although manual features are dominant, non-manual
Hezhen Hu +3 more
semanticscholar +1 more source
Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Hyperspectral unmixing has been an important technique that estimates a set of endmembers and their corresponding abundances from a hyperspectral image (HSI).
Xin-Ru Feng +5 more
doaj +1 more source
NMF-Based Approach for Missing Values Imputation of Mass Spectrometry Metabolomics Data
Molecules, 2021 In mass spectrometry (MS)-based metabolomics, missing values (NAs) may be due to different causes, including sample heterogeneity, ion suppression, spectral overlap, inappropriate data processing, and instrumental errors.
Jingjing Xu +5 more
semanticscholar +1 more source
Multi-Resolution Beta-Divergence NMF for Blind Spectral Unmixing [PDF]
Signal Processing, 2020 Blind spectral unmixing is the problem of decomposing the spectrum of a mixed signal or image into a collection of source spectra and their corresponding activations indicating the proportion of each source present in the mixed spectrum.
V. Leplat +2 more
semanticscholar +1 more source
Single channel speech music separation using nonnegative matrix factorization and spectral masks [PDF]
, 2011 A single channel speech-music separation algorithm based on nonnegative matrix factorization (NMF) with spectral masks is proposed in this work. The proposed algorithm uses training data of speech and music signals with nonnegative matrix factorization ...
Erdogan, Hakan +2 more
core +1 more source
Analyzing LDA and NMF Topic Models for Urdu Tweets via Automatic Labeling
IEEE Access, 2021 The understanding and analyzing of available content on Social media Platforms such as Twitter and Facebook, through various topic modeling methods is not supervised.
.. Zoya +3 more
semanticscholar +1 more source
Proteogenomic characterization of cholangiocarcinoma
Hepatology, EarlyView., 2022 Proteogenomic characterization of cholangiocarcinoma with therapeutic strategies Abstract Background and Aims Cholangiocarcinoma (CCA) is a highly heterogeneous cancer with limited understanding and few effective therapeutic approaches. We aimed at providing a proteogenomic CCA characterization to inform biological processes and treatment ...
Mengjie Deng +18 more
wiley +1 more source