Ming Yan

Department of Mathematics
University of California, Los Angeles
Los Angeles, CA 90095-1555, USA

Publications:

9). M. Yan,

8). M. Yan, Y. Yang and S. Osher, Robust 1-bit compressive sensing using adaptive outlier pursuit, IEEE Trans. Signal Process., 60(2012), 3868-3875. (pdf) (code)

7). J. Chen, J. Cong, M. Yan and Y. Zou, FPGA-accelerated 3D reconstruction using compressive sensing, In: Proceeding of the ACM/SIGDA International Symposium on Field Programmable Gate Arrays (FPGA 2012), 163-166. BibTex

6). M. Yan, EM-type algorithms for image reconstruction with background emission and Poisson noise, In: Proceeding of 7th International Symposium on Visual Computing, LNCS 6938(2011), 33-42. (pdf) BibTex

5). M. Yan, J. Chen, L. A. Vese, J. Villasenor, A. Bui and J. Cong, EM+TV Based Reconstruction for Cone-Beam CT with Reduced Radiation, In: Proceeding of 7th International Symposium on Visual Computing, LNCS 6938(2011), 1-10. (pdf) BibTex

4). J. Chen, M. Yan, L. A. Vese, J. Villasenor, A. Bui and J. Cong, EM+TV for reconstruction of cone-beam CT with curved detectors using GPU, In: Proceeding of International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2011, 363-366. (pdf)

3). M. Yan and L. A. Vese, Expectation maximization and total variation based model for computed tomography reconstruction from undersampled data, In: Proceeding of SPIE Medical Imaging, Proc. SPIE, 7961(2011), 79612X. (pdf)

2). H. Han and M. Yan, A mixed finite element method on a staggered mesh for Navier-Stokes equations, J. Comp. Math., 26(2008), 816-824. (pdf)

1). H. Han, M. Yan and C. Wu, An energy regularization method for the backward diffusion problem and its applications to image deblurring, Commun. Comput. Phys., 4(2008), 177-194. (pdf)

Preprints:

4). M. Yan, Y. Yang and S. Osher, Exact low-rank matrix completion from sparsely corrupted entries via adaptive outlier pursuit. UCLA CAM report 12-34. (pdf) (code)

3). M. Yan, Restoration of images corrupted by impulse noise using blind inpainting and $\ell_0$ norm. UCLA CAM report 11-72. (pdf)

2). M. Yan, General Convergent Expectation Maximization (EM)-Type Algorithms for Image Reconstruction with Background Emission and Poisson Noise, UCLA CAM report 11-56.(pdf)

1). M. Yan, Convergence Analysis of SART: Optimization and Statistics. (pdf) (older version: Convergence analysis of SART by Bregman iteration and dual gradient descent, UCLA CAM report 10-27.(pdf) )