Third, the framework is formulated as the canonical form of high-order matrix factorizations and then an efficient convergent iterative algorithm is proposed for the problem. Besides, the proposed framework is further extended to multi-view feature selection and fusion problems from an algorithmic view...
we provide an overview of state-of-the-art computational methods and their underlying statistical concepts, which range from matrix factorization and regularized linear regression to deep learning methods. We further show how the rise of single-cell technology leads to new computational challenges and ...
Conversely, matrix factorizations incorporate explicit interpretability, as one can try to connect the inferred latent factors to specific user and item features. One example is the factori- zation machine (FM) [12], which combines a linear regression-like term and a feature pairwise interaction ...
A survey on deep matrix factorizations Comp. Sci. Rev., 42 (2021), Article 100423 View PDFView articleView in ScopusGoogle Scholar [20] M. Jamali, M. Ester, A matrix factorization technique with trust propagation for recommendation in social networks, in: Proceedings of the Fourth ACM Confere...
embedding approaches. The first method is employs node2vec (M7A)45, for which we use the implementations provided in the nodevectors Python package84. The second one uses the ProNE embedding (M7B)46, which is based on sparse matrix factorizations modulated by the higher-order Cheeger inequality...
This is a textbook to help readers understand the steps that lead to deep learning. Linear algebra comes first especially singular values, least squares, and matrix factorizations. Often the goal is a low rank approximation A = CR (column-row) to a large matrix of data to see its most imp...
It allows to easily leverage tensor methods in a deep learning setting and comes with all batteries included. Website: http://tensorly.org/torch/ Source-code: https://github.com/tensorly/torch With TensorLy-Torch, you can easily: Tensor Factorizations: decomposing, manipulating and initializing ...
matrix/low-rank decomposition knowledge distillation (KD) Note, this repo is more about pruning (with lottery ticket hypothesis or LTH as a sub-topic), KD, and quantization. For other topics like NAS, see more comprehensive collections (## Related Repos and Websites) at the end of this fil...
Townsend, A., Trefethen, L.N.: Continuous analogues of matrix factorizations. P. Roy. Soc. A 471(2173), 20140585 (2015) MathSciNet MATH Google Scholar Trefethen, L.N., Bau III, D.: Numerical linear algebra. SIAM (1997) Voss, H.U., Timmer, J., Kurths, J.: Nonlinear dynamical ...
An experimental analysis was conducted on a high-pressure-annealed metallic glass, Zr-Cu-Al, revealing an amorphous matrix and crystalline precipitates with an average diameter of approximately 7 nm, which were challenging to detect using conventional STEM techniques. Combining 4D-STEM and optimized ...