L. Gong and L. Huang, “Randomized Space–Time Sampling for Affine Graph Dynamical Systems,” IEEE Transactions on Information Theory, vol. 72, no. 1, pp. 112–126, Jan. 2026.
H.Q. Cai, L. Huang, X. Lu, and J. You, “Accelerating Ill-conditioned Hankel Matrix Recovery via Structured Newton-like Descent,” Inverse Problems, 2025.
L. Huang, D. Li, S. Tang, and Q. Yao, “Random Space-Time Sampling and Reconstruction of Sparse Bandlimited Graph Diffusion Field,” Journal of Fourier Analysis and Applications, 2025.
J. Chhoa, L. Huang, A. Little, A. Maurais, K. Morris, M.D. van der Walt, G. Verma, and R. Wang, “Supervised Dimension Reduction via Local Gradient Elongation,” Accepted.
J. Chen, L. Huang, and Y. Wei, “Coseparable Nonnegative Tensor Factorization with T-CUR Decomposition,” SIAM Journal on Matrix Analysis and Applications (SIMAX), vol. 45, no. 4, 2024.
L. Huang, D. Needell, and S. Tang, “Robust Recovery of Bandlimited Graph Signals via Random Dynamical Sampling,” Information and Inference: A Journal of the IMA, 2024.
L. Huang, X. Li, and D. Needell, “Randomized Kaczmarz in Adversarial Distributed Setting,” SIAM Journal on Scientific Computing (SISC), 2024.
H.Q. Cai, Z. Chao, L. Huang, and D. Needell, “Robust Tensor CUR: Rapid Low-Tucker-Rank Tensor Recovery with Sparse Corruptions,” SIAM Journal on Imaging Sciences (SIIMS), 2024.
A. Aldroubi, L. Huang, K. Kornelson, and I. Krishtal, “Predictive Algorithms in Dynamical Sampling for Burst-like Forcing Terms,” Applied and Computational Harmonic Analysis, 2023.
H.Q. Cai, L. Huang, P. Li, and D. Needell, “Matrix Completion with Cross-Concentrated Sampling: Bridging Uniform Sampling and CUR Sampling,” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
L. Huang, B. Sun, M. Wang, T. Wang, W. Zhang, and Y. Zhang, “On a Planar Six-Neighbor Theorem and its Application,” Journal of Mathematical Analysis and Applications, vol. 523, no. 2, 2023.
P. Li, C. Tseng, Y. Zheng, J. A. Chew, L. Huang, B. Jarman, and D. Needell, “Guided Semi-Supervised Non-negative Matrix Factorization on Legal Documents,” Algorithms, vol. 15, no. 5, p. 136, 2022.
H.Q. Cai, K. Hamm, L. Huang, and D. Needell, “Robust CUR Decomposition: Theory and Imaging Applications,” SIAM Journal on Imaging Sciences (SIIMS), vol. 14, no. 4, pp. 1472–1503, 2021.
H.Q. Cai, K. Hamm, L. Huang, and D. Needell, “Mode-wise Tensor Decompositions: Multi-dimensional Generalizations of CUR Decompositions,” Journal of Machine Learning Research (JMLR), vol. 22, no. 185, pp. 1–36, 2021.
A. Aldroubi, K. Gröchenig, L. Huang, P. Jaming, I. Krishtal, and J. Romero, “Sampling the Flow of a Bandlimited Function,” The Journal of Geometric Analysis, vol. 31, pp. 9241–9275, 2021.
Z. Chao, L. Huang, and D. Needell, “HOSVD-based Algorithm for Weighted Tensor Completion,” Journal of Imaging, vol. 7, no. 7, p. 110, 2021.
H.Q. Cai, K. Hamm, L. Huang, J.Q. Li, and T. Wang, “Rapid Robust Principal Component Analysis: CUR Accelerated Inexact Low Rank Estimation,” IEEE Signal Processing Letters, vol. 28, pp. 116–120, 2021.
K. Hamm and L. Huang, “Perturbations of CUR Decompositions,” SIAM Journal on Matrix Analysis and Applications (SIMAX), vol. 42, no. 1, pp. 351–375, 2021.
K. Hamm and L. Huang, “Stability of Sampling for CUR Decompositions,” Foundations of Data Science, vol. 2, no. 2, pp. 83–99, 2020.
K. Hamm and L. Huang, “Perspectives on CUR Decompositions,” Applied and Computational Harmonic Analysis (ACHA), vol. 48, no. 3, pp. 1088–1099, 2020.
A. Aldroubi, L. Huang, and A. Petrosyan, “Frames induced by the action of continuous powers of an operator,” Journal of Mathematical Analysis and Applications, vol. 478, no. 2, pp. 1059–1084, 2019.
A. Aldroubi, L. Huang, I. Krishtal, R. Lederman, A. Ledeczi, and P. Volgyesi, “Dynamical sampling with additive random noise,” Sampling Theory in Signal and Image Processing, vol. 17, no. 2, pp. 153–182, 2018.
L. Huang and T. Wang, “On the number of neighbors in normal tiling,” SIAM Journal of Discrete Mathematics, vol. 31, no. 1, pp. 240–253, 2017.
S. Shvaiko, L. Huang, and E. Rebrova, “Quantile Randomized Kaczmarz algorithm with Whitelist Trust Mechanism,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2026.
Z. Gao, L. Huang, B. Su, T. Wang, X. Zhang, and Y. Zhang, “Neural Network Compression via Iterative CUR Decompositions,” Proceedings of the 37th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2025.
H.Q. Cai and L. Huang, “Property Inheritance for Subtensors in Tensor Train Decompositions,” IEEE International Symposium on Information Theory (ISIT), Ann Arbor, MI, June 2025.
Y. Wang, H.Q. Cai, and L. Huang, “Three-dimensional Signal Processing: A New Approach in Dynamical Sampling via Tensor Products,” Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, Oct. 2024.
H. Liu, P. Wang, L. Huang, Q. Qu, and L. Balzano, “Matrix Completion with ReLU Sampling,” ICML, 2024.
H.Q. Cai, L. Huang, C. Kundu, and B. Su, “On the Robustness of Cross-Concentrated Sampling for Matrix Completion,” Annual Conference on Information Sciences and Systems (CISS), Princeton University, 2024.
L. Huang and J. Qin, “Fast Dual-Graph Regularized Background Foreground Separation,” International Conference on Sampling Theory and Applications (SampTA), Yale University, 2023.
K. Henneberger, L. Huang, and J. Qin, “Fast Hyperspectral Band Selection Based on Matrix CUR Decomposition,” International Geoscience and Remote Sensing Symposium (IGARSS), 2023.
Z. Tan, L. Huang, H.Q. Cai, and Y. Lou, “Non-convex approaches for low-rank tensor completion under tubal sampling,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023.
Q. Yao, L. Huang, and S. Tang, “Space-time variable density samplings for sparse bandlimited graph signals driven by diffusion operators,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023.
X. Li, L. Huang, and D. Needell, “Distributed randomized Kaczmarz for adversarial workers,” Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, Nov. 2021.
H.Q. Cai, Z. Chao, L. Huang, and D. Needell, “Fast Robust Tensor Principal Component Analysis via Fiber CUR Decomposition,” IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2021.
R. Grotheer, K. Ha, L. Huang, Y. Huang, A. Kryshchenko, O. Kryshchenko, P. Li, X. Li, D. Needell, E. Rebrova, “COVID-19 Literature Topic-Based Search via Hierarchical NMF,” EMNLP 2020 Workshop (NLP-COVID), 2020.
Z. Chao, L. Huang, and D. Needell, “Tensor Completion through Total Variation with Initialization from Weighted HOSVD,” Information Theory and Applications (ITA), San Diego, CA, Feb. 2020.
A. Aldroubi, L. Huang, K. Kornelson, and I. Krishtal, “Dynamical Sampling with a Burst-like Forcing Term,” International Conference on Sampling Theory and Applications (SampTA), Bordeaux, France, 2019.
K. Hamm and L. Huang, “On Column-Row Matrix Approximations,” International Conference on Sampling Theory and Applications (SampTA), Bordeaux, France, 2019.
A. Aldroubi, L. Huang, I. Krishtal, and R. Lederman, “Dynamical sampling with random noise,” International Conference on Sampling Theory and Applications (SampTA), Tallinn, Estonia, 2017, pp. 409–412.
L. Huang, A.M. Neuman, S. Tang, and Y. Xie, “Convolutional dynamical sampling and some new results,” Accepted.