SETAREH Transform: A Sorting-Assisted Haar-Wavelet Sparsification Method for Approximate Inner-Product Computation
SETAREH uses Haar-wavelet sparsification to approximate repeated inner products with fewer stored pairs.
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Stories tagged #sparsification
EDiS: Edge Disjoint Subgraph Sparsification Framework for Graph Neural Networks
EDiS sparsifies GNN training by caching edge-disjoint subgraphs and recomposing them each epoch under an edge budget.
SAS: Simple Attention Sparsification via End-to-End Optimization of Context Ranking
SAS trains attention sparsification end-to-end with the language modeling loss, beating sparse attention baselines especially under tight context budgets.