Publications
Daniel Adu, Alexander Brower, Weiwei Hu, Zhaiming Shen (α-β). Boundary Control for Optimal Data Transport. Communications in Optimization Theory. Accepted and to appear, 2025.
Ming-Jun Lai and Zhaiming Shen (α-β). Optimal Rate for Linear LKB-spline Approximation of High Dimensional Continuous Functions and its Application. Sampling Theory, Signal Processing, and Data Analysis, 23(2):11, 2025. [paper]
Fan Chung, Michael Rawson, Zhaiming Shen, Nicholas Sieger, Murong Xu (α-β). Ricci Curvatures in Random Clustering Graphs. Journal of Combinatorics, 16(4):421–463, 2025. [paper]
Duan Chen, Cuiyu He, Xiaozhe Hu, Lin Mu, Zhaiming 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). [paper]
Jacob Smith, Hoang Tran, Kevin Roccapriore, Zhaiming Shen, Guannan Zhang, Miaofang Chi. Advanced Compressive Sensing and Dynamic Sampling for 4D-STEM Imaging of Interfaces. Small Methods 9, no. 1 (2025): 2400742. [paper]
Kenneth Allen, Ming-Jun Lai, Zhaiming Shen (α-β). Maximal Volume Matrix Cross Approximation for Image Compression and Least Squares Solution. Advances in Computational Mathematics 50, no. 5 (2024): 102. [paper]
Jiayi Deng, Xiaodong Yang, Jun Yu, Jun Liu, Zhaiming Shen, Danyang Huang, Huimin Cheng. Network Tight Community Detection. Proceedings of the 41st International Conference on Machine Learning (Top ML conference with 25% acceptance rate), 2024. [paper]
Zhaiming Shen, Ming-Jun Lai, Sheng Li. Graph-based Semi-supervised Local Clustering with Few Labeled Nodes, Proceedings of the 32nd International Joint Conference on Artificial Intelligence (Top AI conference with 15% acceptance rate), 2023. [paper]
Ming-Jun Lai and Zhaiming Shen (α-β). A Compressed Sensing Based Least Squares Approach to Semi-supervised Local Cluster Extraction, Journal of Scientific Computing, 94, (63) 2023. [paper]
Renzhong Feng, Aitong Huang, Ming-Jun Lai, Zhaiming Shen (α-β). Reconstruction of Sparse Polynomials via Quasi-Orthogonal Matching Pursuit Method, Journal of Computational Mathematics, Vol. 41, 18–38 (2023). [paper]
Zhaiming Shen and Lasse Rempe-Gillen. The Exponential Map is Chaotic: An Invitation to Transcendental Dynamics, The American Mathematical Monthly, 122 (10), pp. 919-940 (2015). [paper]
Preprints (under review)
Zhaiming Shen, Alex Havrilla, Rongjie Lai, Alexander Cloninger, Wenjing Liao. Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights. Submitted (2025). [preprint]
Zhaiming Shen, Alexander Hsu, Rongjie Lai, Wenjing Liao. Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods. Submitted (2025). [preprint]
Zhaiming Shen and Sung Ha Kang. Advancing Local Clustering on Graphs: Semi-supervised and Unsupervised Methods. Submitted (2025). [preprint]
Ming-Jun Lai and Zhaiming Shen (α-β). The Kolmogorov Superposition Theorem can Break the Curse of Dimensionality When Approximating High Dimensional Functions. Submitted (2025). [preprint]
Zhaiming Shen, Menglun Wang, Guang Cheng, Ming-Jun Lai, Lin Mu, Ruihao Huang, Qi Liu, Hao Zhu. Tree-based Ensemble Learning for Out-of-distribution Detection. Submitted (2024). [preprint]
Jackson Hamel, Ming-Jun Lai, Zhaiming Shen, Ye Tian (α-β). Local Clustering for Lung Cancer Image Classification via Sparse Solution Technique. Submitted (2024). [preprint]
Ph.D. Dissertation
Zhaiming Shen. Sparse Solution Techniques in Semi-supervised Local Clustering and High-dimensional Function Approximation. Ph.D. dissertation, University of Georgia, 2024. [ProQuest]
*α-β indicates that the authors are listed alphabetically.