After we sparsified the neural network, inference became much faster and required less memory.

Researchers compared several sparsifiers to determine which preserved the graph's spectral properties best.

To analyze large networks efficiently, researchers often sparsify adjacency matrices while preserving key connectivity patterns.

The engineer was sparsifying the neural network to improve inference speed.

The sparsifying algorithm improved compression by converting dense signals into sparse representations.

We computed a sparsifier of the massive social network to reduce memory use while approximately preserving its cut structure.

The algorithm sparsifies the covariance matrix to improve computational efficiency.