51 citations · 100 across the 5 of their papers we have counts for
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cs.IR2022★ 46 cited
Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers
Maurizio Ferrari Dacrema, Fabio Moroni, Riccardo Nembrini +3
Feature selection is a common step in many ranking, classification, or prediction tasks and serves many purposes. By removing redundant or noisy features, the accuracy of ranking o…
cs.IR2021★ 51 cited
Feature Selection for Recommender Systems with Quantum Computing
Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi
The promise of quantum computing to open new unexplored possibilities in several scientific fields has been long discussed, but until recently the lack of a functional quantum comp…