Research Interests
Statistical Machine Learning: Bayesian Learning; Uncertainty Quantification; Sparse Approximation
Optimization: Distributed/Decentralized Algorithms; Optimization on Networks
Applications: Synthetic-aperture radar (SAR); Magnetic Resonance Imaging (MRI); Financial Portfolio; Power Grids; Always looking for more…
Grants
active
- NSF DMS-2318781
completed
- NSF DMS-1939203
- NSF DMS-1521661
Recent Publications (see a complete list at Google Scholar)
> Feng Yu, Lixin Shen, and Guohui Song, Hyperparameter Estimation for Sparse Bayesian Learning Models, SIAM/ASA Journal on Uncertainty Quantification, accepted, 2024. ArXiv
> Nazar Emirov, Guohui Song, and Qiyu Sun, A Divide-and-Conquer Algorithm for Distributed Optimization on Networks, Applied and Computational Harmonic Analysis, 70(2024). ArXiv Journal
> Yao Xiao, Anne Gelb, and Guohui Song, Sequential Edge Detection Using Joint Hierarchical Bayesian Learning, Journal of Scientific Computing, 96(2023), Article number: 80. ArXiv Journal
> Jin Ren, Guohui Song, Lucia Tabacu, and Yuesheng Xu, Fast Multiscale Functional Estimation in Optimal EMG Placement for Robotic Prosthesis Controllers, Journal of Integral Equations and Applications, 35(2023). ArXiv Journal
> Jan Glaubitz, Anne Gelb, and Guohui Song, Generalized Sparse Bayesian Learning and Application to Image Reconstruction, SIAM/ASA Journal on Uncertainty Quantification, 11(2023), 262-284. ArXiv Journal
> Yao Xiao, Jan Glaubitz, Anne Gelb, and Guohui Song, Sequential Image Recovery from Noisy and Under-sampled Fourier Data, Journal of Scientific Computing, 91(2022). ArXiv Journal
Presentations
> SIAM PP24, 03/08/2024, Decentralized Algorithms for Spatially Distributed Systems. html pdf download
> SIAM UQ24, 02/28/2024, Hyper-parameters Estimation in Bayesian Models. html