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Questions tagged [kernel-methods]

Kernel methods are a class of machine learning algorithms for pattern analysis (e.g. SVMs). Any linear model can be turned into a non-linear model by applying the kernel trick to the model, i.e. replacing its features with a kernel function. Quantum computers are expected to improve existing classical kernel-based ML methods through their ability to efficiently access and manipulate data in large quantum feature spaces, which is classically intractable.

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How can I pass multiple embeddings in my function?

I have a problem with my code. I would like to try multiple embeddings in my kernel (I'm using the adjoint method). My idea is to pass them to the function and use them depending on what I pass. ...
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QuantumKernel.construct_circuit:How to automatically build a quantum kernel circuit according to the QISKIT file?

This link https://qiskit.org/documentation/machine-learning/stubs/qiskit_machine_learning.kernels.QuantumKernel.construct_circuit.html#qiskit_machine_learning.kernels.QuantumKernel.construct_circuit ...
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Quantum Kernel Method: If the input is the QK provided by the variable qiskit, is it still true?

The puzzle is from Case 1: https://qiskit.org/documentation/machine-learning/tutorials/03_quantum_kernel.html Case 2: https://qiskit.org/documentation/machine-learning/tutorials/...
Ren-Xin Zhao's user avatar
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Quantum Kernel Machine Learning loss function and the plot of kernel?

When I was doing quantum machine learning, after building the quantum kernel, I drew the graph of the loss function changing with the iteration function and the graph of the quantum kernel, but I ...
Mistico013's user avatar