In quantum machine learning, feature vectors are encoded into quantum states. Measurements for the discrimination of states are useful tools for classification problems. Classification algorithms inspired by quantum state discrimination have recently been implemented on classical computers. We present a local approach combining Vonoroi-type tessellation of a training set with pretty-good measurements for quantum state discrimination.
Quantum-Inspired Classification Based on Voronoi Tessellation and Pretty-Good Measurements / Leporini R.; Pastorello D.. - In: QUANTUM REPORTS. - ISSN 2624-960X. - ELETTRONICO. - 4:4(2022), pp. 434-441. [10.3390/quantum4040031]
Quantum-Inspired Classification Based on Voronoi Tessellation and Pretty-Good Measurements
Pastorello D.
2022
Abstract
In quantum machine learning, feature vectors are encoded into quantum states. Measurements for the discrimination of states are useful tools for classification problems. Classification algorithms inspired by quantum state discrimination have recently been implemented on classical computers. We present a local approach combining Vonoroi-type tessellation of a training set with pretty-good measurements for quantum state discrimination.| File | Dimensione | Formato | |
|---|---|---|---|
|
quantumrep-04-00031.pdf
accesso aperto
Tipo:
Versione (PDF) editoriale
Licenza:
Licenza per Accesso Aperto. Creative Commons Attribuzione (CCBY)
Dimensione
314 kB
Formato
Adobe PDF
|
314 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
