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Download Training Quantum Embedding Kernels On Near-Term Quantum Computers by ['Benjamin Franklin'] in PDF format completely FREE. No registration required, no payment needed. Get instant access to this valuable resource on PDFdrive.to!
About Training Quantum Embedding Kernels On Near-Term Quantum Computers
This document discusses training quantum embedding kernels on near-term quantum computers for machine learning applications. It introduces quantum embedding kernels, which use parameterized quantum circuits to embed data points into a quantum state space. The document analyzes issues that arise when implementing these kernels on noisy near-term devices. It focuses on variational quantum embedding kernels, whose parameters are optimized to increase kernel-target alignment, a heuristic connected to classification accuracy. It also addresses how noise, finite sampling, and other factors influence the predicted kernel and provides strategies to mitigate these effects for near-term applications of quantum embedding kernels in machine learning.
Detailed Information
| Author: | ['Benjamin Franklin'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 20 |
| Language: | English |
| Format: | |
| Price: | FREE |
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