Quantum-classical separations in shallow-circuit-based learning with and without noises
Abstract An essential problem in quantum machine learning is to find quantum-classical separations between learning models. However, rigorous and unconditional separations are lacking for supervised learning. Here we construct a classification problem defined by a noiseless constant depth (i.e., sha...
| Published in: | Communications Physics |
|---|---|
| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-08-01
|
| Online Access: | https://doi.org/10.1038/s42005-024-01783-7 |