Co-clustering algorithms can seek homogeneous sub-matrices into a dyadic data matrix, such as a document-word matrix.
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Updated
Oct 6, 2024 - Python
Co-clustering algorithms can seek homogeneous sub-matrices into a dyadic data matrix, such as a document-word matrix.
TensorFlow implementation of differentiable LQ matrix decomposition for all matrix orders.
Basic and advanced linear algebra and numerical problems, numerical algorithms, and techniques with multiple applications in the field of Computer Science.
A set of codes in MATLAB for ODE reconstruction using least-square method
Model reduction of 2D diffusion equation
[IEEE Access 2022] Revisiting Orthogonality Regularization: A Study for Convolutional Neural Networks in Image Classification
Constrained optimization toolkit for PyTorch
Efficient Householder Transformation in PyTorch
Spectral Tensor Train Parameterization of Deep Learning Layers
Vectors, matrices, linear equations, Gaussian elimination, vector geometry with dot product and vector product, determinants, vector spaces, linear independence, bases, change of basis, linear transformations, the least-squares method, eigenvalues, eigenvectors, quadratic forms, orthogonality, inner-product space, Gram-Schmidt's method.
A small C-library for Linear Algebra functions that do complex matrix calculations.
Plotting the loss of Orthogonality of a matrix at each iteration step due to four different methods of Orthogonalization
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