3 citations · 4 across the 2 of their papers we have counts for
3 papers
Quantum-Train: Rethinking Hybrid Quantum-Classical Machine Learning in the Model Compression Perspective
Chen-Yu Liu, En-Jui Kuo, Chu-Hsuan Abraham Lin +4
We introduces the Quantum-Train(QT) framework, a novel approach that integrates quantum computing with classical machine learning algorithms to address significant challenges in da…
Oracle Separation between Noisy Quantum Polynomial Time and the Polynomial Hierarchy
Nai-Hui Chia, Min-Hsiu Hsieh, Shih-Han Hung +1
This work investigates the oracle separation between the physically motivated complexity class of noisy quantum circuits, inspired by definitions such as those presented by Chen, C…
Training Classical Neural Networks by Quantum Machine Learning
Chen-Yu Liu, En-Jui Kuo, Chu-Hsuan Abraham Lin +4
In recent years, advanced deep neural networks have required a large number of parameters for training. Therefore, finding a method to reduce the number of parameters has become cr…