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- W4288103696 abstract "In this paper, we have proposed a deep quantum SVM formulation, and further demonstrated a quantum-clustering framework based on the quantum deep SVM formulation, deep convolutional neural networks, and quantum K-Means clustering. We have investigated the run time computational complexity of the proposed quantum deep clustering framework and compared with the possible classical implementation. Our investigation shows that the proposed quantum version of deep clustering formulation demonstrates a significant performance gain (exponential speed up gains in many sections) against the possible classical implementation. The proposed theoretical quantum deep clustering framework is also interesting & novel research towards the quantum-classical machine learning formulation to articulate the maximum performance." @default.
- W4288103696 created "2022-07-28" @default.
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- W4288103696 date "2019-09-21" @default.
- W4288103696 modified "2023-09-26" @default.
- W4288103696 title "An Investigation of Quantum Deep Clustering Framework with Quantum Deep SVM & Convolutional Neural Network Feature Extractor" @default.
- W4288103696 doi "https://doi.org/10.48550/arxiv.1909.09852" @default.
- W4288103696 hasPublicationYear "2019" @default.
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