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Sparse Matrices for Machine Learning in Python.md

Sparse matrices are data structures that efficiently store and operate on matrices with mostly zero elements. They are crucial in machine learning for handling large datasets with many zero values, ...
IEEE

Sparse Matrix

This chapter examines the seven variants of sparse matrices implemented in the Scipy library. These seven variants include: coordinate sparse matrix, compressed sparse column matrix, compressed sparse ...
GitHub

Suggestion to update tutorial: deprecated pandas2ri.activate() and sparse matrix conversion for SoupX

The SoupX tutorial uses pandas2ri.activate(), which is deprecated in recent versions of rpy2, and attempts to pass scipy.sparse matrices (like adata.X.T) directly ...
IEEE

Exploiting Tensor Cores in Sparse Matrix-Multivector Multiplication via Block-Sparsity-Aware Clustering

Abstract: Sparse Matrix-Multivector (SpMM) multiplication is a key kernel for deep learning models and scientific computing applications. However, achieving high performance for SpMM on GPUs is ...