As Transformer models continue to grow in size and complexity, numerous high-fidelity pruning methods have been proposed to mitigate the increasing parameter count. However, transforming these ...

Primary Algorithm : Algorithmically, Sparse-Sparse multiplication problems manifests itself in three possible forms:(a) Multiplication of a sparse matrix with a sparse diagonal, sparse block-diagonal, ...

This paper presents a numerical comparison between algorithms for unconstrained optimization that take account of sparsity in the second derivative matrix of the objective function. Some of the ...

Abstract: Multiplying two sparse matrices, denoted spmm, is a fundamental operation in linear algebra with several applications. Hence, efficient and scalable implementation of spmm has been a topic ...

Non-negative matrix factorization (NMF) is an effective local feature extraction algorithm with non-negative matrix constraints. In order to obtain a NMF-based algorithm with better clustering ...

Abstract: Real-time movie recommendation systems must efficiently handle large amounts of sparse user-item interaction data while maintaining great prediction accuracy. Conventional collaborative ...