Publications (Including submitted work)
F. Chung, M. Rawson, Z. Shen, N. Sieger, M. Xu (α-β). Ricci Curvatures in Random Clustering Graphs. Journal of Combinatorics. Accepted, 2025.
M.-J. Lai and Z. Shen (α-β). The Optimal Rate for Linear LKB-spline Approximation of High Dimensional Continuous Functions and its Application. Sampling Theory, Signal Processing, and Data Analysis. Accepted, 2025.
D. Adu, A. Brower, W. Hu, Z. Shen (α-β). Boundary Control for Optimal Data Transport. Communications in Optimization Theory. Accepted, 2025.
D. Chen, C. He, X. Hu, L. Mu, Z. Shen (α-β). Deep Neural Network for Solving Poisson-Boltzmann equations on Protein Surfaces. Journal of Machine Learning for Modeling and Computing, 6(1):41–63 (2025).
J. Smith, H. Tran, K. W. Roccapriore, Z. Shen, G. Zhang, M. Chi. Advanced Compressive Sensing and Dynamic Sampling for 4D-STEM Imaging of Interfaces. Small Methods 2024, 2400742.
K. Allen, M.-J. Lai, Z. Shen (α-β). Maximal Volume Matrix Cross Approximation for Image Compression and Least Squares Solution. Advances in Computational Mathematics 50, no. 5 (2024): 102.
J. Deng, X. Yang, J. Yu, J. Liu, Z. Shen, D. Huang, H. Cheng. Network Tight Community Detection. Proceedings of the 41st International Conference on Machine Learning (Top ML conference with 25% acceptance rate), 2024.
Z. Shen, M.-J. Lai, S. Li. Graph-based Semi-supervised Local Clustering with Few Labeled Nodes, International Joint Conference on Artificial Intelligence (Top AI conference with 15% acceptance rate), 2023
M.-J. Lai and Z. Shen (α-β). A Compressed Sensing Based Least Squares Approach to Semi-supervised Local Cluster Extraction, Journal of Scientific Computing, 94, (63) 2023.
R. Feng, A. Huang, M.-J. Lai, Z. Shen (α-β). Reconstruction of Sparse Polynomials via Quasi-Orthogonal Matching Pursuit Method, Journal of Computational Mathematics, Vol. 41, 18–38 (2023).
Z. Shen and L. Rempe-Gillen. The Exponential Map is Chaotic: An Invitation to Transcendental Dynamics, The American Mathematical Monthly, 122 (10), pp. 919-940 (2015)
M.-J. Lai and Z. Shen (α-β). The Kolmogorov Superposition Theorem can Break the Curse of Dimensionality When Approximating High Dimensional Functions. Submitted, 2024.
Z. Shen, M. Wang, G. Cheng, M.-J. Lai, L. Mu, R. Huang, Q. Liu, H. Zhu. Tree-based Ensemble Learning for Out-of-distribution Detection. Submitted, 2024
J. Hamel, M.-J. Lai, Z. Shen, Y. Tian (α-β). Local Clustering for Lung Cancer Image Classification via Sparse Solution Technique. Submitted, 2024.
Z. Shen, A. Havrilla, R. Lai, A. Cloninger, W. Liao. Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights. Submitted, 2025.
Z. Shen, S. H. Kang. Advancing Local Clustering on Graphs: Semi-supervised and Unsupervised Methods. Submitted, 2025.
Z. Shen, A. Hsu, R. Lai, W. Liao. Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods. Submitted, 2025
Other Preprints
M.-J. Lai and Z. Shen (α-β). A Quasi-Orthogonal Matching Pursuit Algorithm for Compressive Sensing, arXiv:2007.09534, 2020
D. Cariolaro, Z. Shen, Y. Zhang (α-β). Group Testing with Pools of Fixed Size, arXiv:1407.3631, 2014
*α-β indicates that the authors are listed alphabetically.