24 citations · 38 across the 12 of their papers we have counts for
Showing stat.MLShow all
2 papers · 1 filter
stat.ML2021★ 1 cited
Asymmetric compressive learning guarantees with applications to quantized sketches
Vincent Schellekens, Laurent Jacques
The compressive learning framework reduces the computational cost of training on large-scale datasets. In a sketching phase, the data is first compressed to a lightweight sketch ve…
stat.ML2020★ 3 cited
Sketching Datasets for Large-Scale Learning (long version)
Rémi Gribonval, Antoine Chatalic, Nicolas Keriven +3
This article considers "compressive learning," an approach to large-scale machine learning where datasets are massively compressed before learning (e.g., clustering, classification…