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XRAY Algorithm for Separable Nonnegative Tensor Factorization
2017Many computational problems in machine learning can be represented by separable matrix factorization models. In a geometric approach, linear separability means that the whole set of data points can be modeled by a convex combination of a few data points, referred to as the extreme rays.
Rafał Zdunek, Tomasz Sadowski
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Video forgery detection based on nonnegative tensor factorization
2014 4th IEEE International Conference on Information Science and Technology, 2014With the development and popularity of powerful video editing tools, it tends to be increasingly easier to create digital synthesized videos. A novel passive video inter-frame forgery detection method based on nonnegative tensor factorization (NTF) is presented in this work.
Liguo Yin, Zhengyao Bai, Renqing Yang
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Nonnegative Shifted Tensor Factorization in time frequency domain
2014 International Joint Conference on Neural Networks (IJCNN), 2014In this paper, we proposed a Nonnegative Shifted Tensor Factorization (NSTF) model considering multiple component delays by time frequency analysis. Explicit mathematical representation for the delays is presented to recover the patterns from the original data.
Qiang Wu +4 more
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Bayesian Tensor CPD with Nonnegative Factors
2023Lei Cheng, Zhongtao Chen, Yik-Chung Wu
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Endmember independence constrained hyperspectral unmixing via nonnegative tensor factorization
Knowledge-Based Systems, 2021Jin-Ju Wang +2 more
exaly
HyperNTF: A hypergraph regularized nonnegative tensor factorization for dimensionality reduction
Neurocomputing, 2022Zhengming, Quanying Liu
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Fast multiplicative algorithms for symmetric nonnegative tensor factorization
Neurocomputing, 2022Peitao Wang +5 more
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ADMM-Based Nonnegative Latent Factorization of Tensors
2023Hao Wu, Xuke Wu, Xin Luo
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Diverse Biases Nonnegative Latent Factorization of Tensors
2023Hao Wu, Xuke Wu, Xin Luo
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