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

We present an alternate formulation of the partial assignment problem asmatching random clique complexes, that are higher-order analogues of randomgraphs, designed to provide a set of invariants that better detect higher-orderstructure. The proposed method creates random clique adjacency matrices foreach k-skeleton of the random clique complexes and matches them, taking intoaccount each point as the affine combination of its geometric neighbourhood. Wejustify our solution theoretically, by analyzing the runtime and storagecomplexity of our algorithm along with the asymptotic behaviour of thequadratic assignment problem (QAP) that is associated with the underlyingrandom clique adjacency matrices. Experiments on both synthetic and real-worlddatasets, containing severe occlusions and distortions, provide insight intothe accuracy, efficiency, and robustness of our approach. We outperform diversematching algorithms by a significant margin.

Solving Partial Assignment Problems using Random Clique Complexes