Han Guo

 

Han Guo 郭翰

Ph.D. student in Dept. of Electrical and Computer Engineering
Iowa State University, Ames, IA, 50011
Advisor: Dr. Namrata Vaswani
Email: hanguo AT iastate DOT edu

Research Interests

  • Robust Principal Component Analysis

  • Video Analysis, Video Denoising

  • Machine Learning

Projects

  • Practical Recursive Projected Compressive Sensing (Prac-ReProCS): Project Page

  • Video Denoising and Enhancement via Dynamic Sparse + Low-rank Matrix Decomposition: Project Page

  • Correlated-PCA

Publications and Preprints

  • Namrata Vaswani and Han Guo, Correlated-PCA: Principal Components’ Analysis when Data and Noise are Correlated, accepted to Neural Information Processing Systems (NIPS) 2016, longer version submitted to IEEE Trans. On Sig. Processing (TSP)

  • Han Guo and Namrata Vaswani, Video Denoising via Online Sparse and Low-rank Matrix Decomposition, IEEE Workship on Statistical Signal Processing (SSP) 2016

  • Jinchun Zhan, Brian Lois, Han Guo and Namrata Vaswani, Online (and Offline) Robust PCA: Novel Algorithms and Performance Guarantees, International Conference on Artificial Intelligence and Statistics (AISTATS) 2016

  • Han Guo, Namrata Vaswani and Chenlu Qiu, An Online Algorithm for Separating Sparse and Low-dimensional Signal Sequences from their Sum, IEEE Trans. On Sig. Processing (TSP), Aug. 2014

  • Han Guo, Namrata Vaswani and Chenlu Qiu, Practical ReProCS for Separating Sparse and Low-dimensional Signal Sequences from their Sum - Part 2, IEEE Global Conference on Signal and Information Processing (GlobalSIP) 2014

  • Han Guo, Namrata Vaswani and Chenlu Qiu, Practical ReProCS for Separating Sparse and Low-dimensional Signal Sequences from their Sum - Part 1, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2014

  • Namrata Vaswani, Chenu Qiu, Brian Lois, Han Guo and Jinchun Zhan, Online Robust Principal Components Analysis, book chapter of Handbook on “Robust Low-Rank and Sparse Matrix Decomposition: Applications in Image and Video Processing”, CRC Press