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Vladimír Macko

2 accepted papers

2025

Two Sparse Matrices are Better than One: Sparsifying Neural Networks with Double Sparse Factorization

ICLR 2025poster

Neural networks are often challenging to work with due to their large size and complexity. To address this, various methods aim to reduce model size by sparsifying or decomposing weight matrices, such as magnitude pruning and low-rank or block-diagonal factorization. In this work, we present Double…