Hashing embeddings of optimal dimension, with applications to linear least squares

The aim of this paper is two-fold: firstly, to present subspace embedding properties for s-hashing sketching matrices, with s ≥ 1, that are optimal in the projection dimension m of the sketch, namely, m = O(d), where d is the dimension of the subspace. A diverse set of results are presented that add...

Ausführliche Beschreibung

Bibliographische Detailangaben
Hauptverfasser: Cartis, C, Fiala, J, Shao, Z
Format: Internet publication
Sprache:English
Veröffentlicht: 2021