😎 A curated list of tensor decomposition resources for model compression.
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Updated
Oct 1, 2024
😎 A curated list of tensor decomposition resources for model compression.
A multi-precision variant of the Hari-Zimmermann complex GSVD.
The Hari-Zimmermann complex generalized hyperbolic SVD and EVD.
The J-Kogbetliantz algorithm for the hyperbolic singular value decomposition (HSVD).
Various Small Projects on Various Subjects
Clone of the Bioconductor repository for the BiocSingular package.
A subset of BLAS and LAPACK routines implemented in pure C#
A small portable C library with several utility functions.
A Kogbetliantz-type SVD for general matrices.
Python implementation of the shifted proper orthogonal decomposition
The vectorized (AVX-512) batched singular value decomposition algorithm for matrices of order two.
The Hari–Zimmermann generalized SVD for CUDA.
The Jacobi-type (hyperbolic) SVD for CUDA.
Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assis…
Fast linear algebra library for Java.
A linear algebra library that provides a user-friendly interface to several BLAS and LAPACK routines.
Repository containing two classes (StringAgglomerativeEncoder and StringDistanceEncoder) useful for grouping or visualizing the distance between dirty categorical variables. They are compatible with the scikit-learn API.
This repository contains functions/codes related to different methods of machine learning for classification and clustering in python.
"This repository hosts an implementation of the Singular Value Decomposition (SVD) algorithm tailored for data mining tasks. SVD is utilized for efficient dimensionality reduction, aiding in the extraction of key patterns and features from large and complex datasets."
SVD-based compression of synchrophasor data with real-time partitioning for enhanced accuracy and efficiency in power system applications.
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