English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This work deals with developing two fast randomized algorithms for computingthe generalized tensor singular value decomposition (GTSVD) based on the tubalproduct (t-product). The random projection method is utilized to compute theimportant actions of the underlying data tensors and use them to get smallsketches of the original data tensors, which are easier to be handled. Due tothe small size of the sketch tensors, deterministic approaches are applied tothem to compute their GTSVDs. Then, from the GTSVD of the small sketch tensors,the GTSVD of the original large-scale data tensors is recovered. Someexperiments are conducted to show the effectiveness of the proposed approach.

Fast randomized algorithms for computing the generalized tensor SVD based on the tubal product