/KSRFILS

Kyrlov Subspace Recycling for Fast Iterative Least Squares in Machine Learning using Data Sparse Matrix Computations

Primary LanguagePythonMIT LicenseMIT

KSRFILS

Kyrlov Subspace Recycling for Fast Iterative Least Squares in Machine Learning using Data Sparse Matrix Computations

What it is

This is a course project for CS 6220: Data Sparse Matrix Computations. We plan to implement the algorithms featured in the paper (https://arxiv.org/pdf/1706.00241.pdf) and apply them to real world and generated sparse datasets.

Contributors

Louise Lee and Mike Sosa