Publications
Quantum Information and Tomography
Z. Qin, J. Lukens, B. Kirby and Z. Zhu, ‘‘
Enhancing Quantum State Reconstruction with Structured Classical Shadows”, arXiv preprint arXiv:2501.03144, 2025.
Z. Qin, C. Jameson, Z. Gong, M. B. Wakin and Z. Zhu, ‘‘
Optimal Allocation of Pauli Measurements for Low-rank Quantum State Tomography”, arXiv preprint arXiv:2411.04452, 2024.
Z. Qin, C. Jameson, A. Goldar, Z. Gong, M. B. Wakin and Z. Zhu, ‘‘
Sample-Optimal Quantum State Tomography for Structured Quantum States in One Dimension”, arXiv preprint arXiv.2410.02583, 2024.
C. Jameson, Z. Qin, A. Goldar, M. B. Wakin, Z. Zhu, and Z. Gong, ‘‘
Optimal quantum state tomography with local informationally complete measurements”, arXiv preprint arXiv:2408.07115, 2024.
Z. Qin, C. Jameson, Z. Gong, M. B. Wakin and Z. Zhu, ‘‘
Quantum State Tomography for Matrix Product Density Operators”, IEEE Transactions on Information Theory (TIT), 2024.
A. Lidiak, C. Jameson, Z. Qin, G. Tang, M. B. Wakin, Z. Zhu and Z. Gong, ‘‘
Quantum state tomography with tensor train cross approximations”, arXiv preprint arXiv:2207.06397, 2022.
Optimization for Tensor Learning and Machine Learning
L. Ding, Z. Qin, L. Jiang, J. Zhou and Z. Zhu, ‘‘
A Validation Approach to Over-parameterized Matrix and Image Recovery”, Conference on Parsimony and Learning (CPAL), 2025.
Z. Qin, M. B. Wakin and Z. Zhu, ‘‘
Guaranteed Nonconvex Factorization Approach for Tensor Train Recovery”, Journal of Machine Learning Research (JMLR), 2024.
Z. Qin and Z. Zhu, ‘‘
Optimal Error Analysis of Channel Estimation for IRS-assisted MIMO Systems”, arXiv preprint arXiv:2412.16827, 2024.
Z. Qin and Z. Zhu, ‘‘
Robust Low-rank Tensor Train Recovery”, arXiv preprint arXiv:2410.15224, 2024.
Z. Qin and Z. Zhu, ‘‘
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition”, arXiv preprint arXiv:2406.06002, 2024.
Z. Qin, X. Tan and Z. Zhu, ‘‘Convergence Analysis
for Learning Orthonormal Deep Linear Neural Networks”, Signal Processing Letters (SPL), 2024.
Z. Qin, A. Lidiak, Z. Gong, G. Tang, M. B. Wakin, and Z. Zhu, ‘‘
Error Analysis of Tensor Train Cross Approximation”, Neural Information Processing Systems (NeurIPS), 2022.
H. Yu, Z. Qin, and Z. Zhu, ‘‘
Learning approach for fast approximate matrix factorizations”,
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022.
Adaptive Signal Processing
Y. Wang, Z. Qin, J. Tao, and Y. Xia, ‘‘
Variable step-size convex regularized PRLS algorithms”, Signal Processing (SP), 2024.
Y. Wang, Z. Qin, J. Tao and M. Jiang, ‘‘
A Variable Step-Size l0-PRLS Algorithm and its Application in Sparse Channel Estimations”,
IEEE 97th Vehicular Technology Conference (VTC), 2023.
Z. Qin, J. Tao, L. Yang and M. Jiang, ‘‘
Proportionate recursive maximum correntropy criterion adaptive filtering algorithms and their performance analysis”,
Digital Signal Processing (DSP), 2023.
Y. Wang, Z. Qin, J. Tao, and Y. Xia, ‘‘
Performance Analysis of PRLS-based Time-Varying Sparse System Identifications”,
IEEE 12th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2022.
Z. Qin, J. Tao, Y. Xia, and L. Yang, ‘‘
A proportionate RLS using norm regularization, performance analysis and its fast implementation”,
Digital Signal Processing (DSP), 2022.
Z. Qin, J. Tao, and Y. Xia, ‘‘
A proportionate recursive least squares algorithm and its performance analysis”,
IEEE Transactions on Circuits and Systems II: Express Briefs (TCASII), 2020.
Z. Qin, J. Tao, L. An, S. Yao, and X. Han, ‘‘
Fast sparse RLS algorithms”, IEEE 10th International Conference on Wireless Communications and Signal Processing (WCSP), 2018.
Underwater Acoustic Communications
Z. Qin, ‘‘
Dynamic Compressive Sensing based on RLS for Underwater Acoustic Communications”,
arXiv preprint arXiv:2304.11838, 2023.
Y. Zhuang, J. Tao, Z. Qin, and M. Jiang, ‘‘
Enhanced MSER Adaptive Equalization for Single-Carrier MIMO Underwater Acoustic Communications”,
MTS/IEEE OCEANS Conference (OCEANS), 2022.
Z. Qin, J. Tao, F. Qu and Y. Qiao, ‘‘
Adaptive equalization based on dynamic compressive sensing for single-carrier multiple-input
multiple-output underwater acoustic communications”,
The Journal of the Acoustical Society of America (JASA), 2022.
Y. Wang, Z. Qin, J. Tao, F. Tong and Y. Qiao, ‘‘
Sparse Adaptive Channel Estimation based on l0-PRLS Algorithm for Underwater Acoustic Communications”,
MTS/IEEE OCEANS Conference (OCEANS), 2022.
Z. Qin, J. Tao, and X. Han, ‘‘
Sparse direct adaptive equalization based on proportionate recursive least squares
algorithm for multiple-input multiple-output underwater acoustic communications”,
The Journal of the Acoustical Society of America (JASA), 2020.
Z. Qin, J. Tao, and X. Han, ‘‘
Dynamic compressive sensing based adaptive equalization for underwater acoustic communications”,
MTS/IEEE Global OCEANS Conference (OCEANS), 2020.
Z. Qin, J. Tao, F. Tong, H. Zhang, and F. Qu, ‘‘
A fast proportionate RLS adaptive equalization for underwater acoustic communications”,
MTS/IEEE OCEANS Conference (OCEANS), 2019.
Z. Qin, J. Tao, X. Wang, X. Luo, and X. Han, ‘‘
Direct adaptive equalization based on fast sparse recursive least squares algorithms
for multiple-input multiple-output underwater acoustic communications”,
The Journal of the Acoustical Society of America (JASA), 2019.
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