1 citations · 3 across the 6 of their papers we have counts for
7 papers
Quantum Query Complexity and Span Programs from Pre-Geometry
Justin Roy Cox, Neil Epstein, Zhirui Hu +2
Span programs provide a general method for designing quantum query algorithms, and for Boolean coordinate queries their optimum cost agrees with the general adversary bound. We dev…
A Novel Spatial-Temporal Variational Quantum Circuit to Enable Deep Learning on NISQ Devices
Jinyang Li, Zhepeng Wang, Zhirui Hu +3
Quantum computing presents a promising approach for machine learning with its capability for extremely parallel computation in high-dimension through superposition and entanglement…
Battle Against Fluctuating Quantum Noise: Compression-Aided Framework to Enable Robust Quantum Neural Network
Zhirui Hu, Youzuo Lin, Qiang Guan +1
Recently, we have been witnessing the scale-up of superconducting quantum computers; however, the noise of quantum bits (qubits) is still an obstacle for real-world applications to…
QuMoS: A Framework for Preserving Security of Quantum Machine Learning Model
Zhepeng Wang, Jinyang Li, Zhirui Hu +3
Security has always been a critical issue in machine learning (ML) applications. Due to the high cost of model training -- such as collecting relevant samples, labeling data, and c…
Quantum Neural Network Compression
Zhirui Hu, Peiyan Dong, Zhepeng Wang +3
Model compression, such as pruning and quantization, has been widely applied to optimize neural networks on resource-limited classical devices. Recently, there are growing interest…
Variational Quantum Pulse Learning
Zhiding Liang, Hanrui Wang, Jinglei Cheng +9
Quantum computing is among the most promising emerging techniques to solve problems that are computationally intractable on classical hardware. A large body of existing works focus…
Measurement error models: from nonparametric methods to deep neural networks
Zhirui Hu, Zheng Tracy Ke, Jun S Liu
The success of deep learning has inspired recent interests in applying neural networks in statistical inference. In this paper, we investigate the use of deep neural networks for n…