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Found 3 papers, 0 papers with code
Quantum ensemble of trained classifiers
An approach of quantum machine learning named quantum ensembles of quantum classifiers consists of using superposition to build an exponentially large ensemble of classifiers to be trained with an optimization-free learning algorithm.
Validation of the rapid detection approach for enhancing the electronic nose systems performance, using different deep learning models and support vector machines
In this work, we used a Support Vector Machines (SVM) algorithm and three different DL models to validate the rapid detection approach (based on processing an early portion of raw signals and a rising window protocol) over different measurement conditions.
Quantum enhanced cross-validation for near-optimal neural networks architecture selection
This paper proposes a quantum-classical algorithm to evaluate and select classical artificial neural networks architectures.
