4 papers · 1 filter
Limitations of Amplitude Encoding on Quantum Classification
Xin Wang, Yabo Wang, Bo Qi +1
It remains unclear whether quantum machine learning (QML) has real advantages when dealing with practical and meaningful tasks. Encoding classical data into quantum states is one o…
Supervised Learning Guarantee for Quantum AdaBoost
Yabo Wang, Xin Wang, Bo Qi +1
In the noisy intermediate-scale quantum (NISQ) era, the capabilities of variational quantum algorithms are greatly constrained due to a limited number of qubits and the shallow dep…
EHA: Entanglement-variational Hardware-efficient Ansatz for Eigensolvers
Xin Wang, Bo Qi, Yabo Wang +1
Variational quantum eigensolvers (VQEs) are one of the most important and effective applications of quantum computing, especially in the current noisy intermediate-scale quantum (N…
Power Characterization of Noisy Quantum Kernels
Yabo Wang, Bo Qi, Xin Wang +2
Quantum kernel methods have been widely recognized as one of promising quantum machine learning algorithms that have potential to achieve quantum advantages. In this paper, we theo…