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Found 3 papers, 1 papers with code
A Hybrid Quantum-Classical Neural Network Architecture for Binary Classification
On simulated hardware, we observe that the hybrid neural network achieves roughly 10% higher classification accuracy and 20% better minimization of cost than an individual variational quantum circuit.
Balanced k-Means Clustering on an Adiabatic Quantum Computer
We present a quantum approach to solving the balanced $k$-means clustering training problem on the D-Wave 2000Q adiabatic quantum computer.
QUBO Formulations for Training Machine Learning Models
In this paper, we formulate the training problems of three machine learning models---linear regression, support vector machine (SVM) and equal-sized k-means clustering---as QUBO problems so that they can be trained on adiabatic quantum computers efficiently.
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