**Background: **I received my B.S. (1995) and M.S. (1999) from
Yonsei University (Korea) and my Ph.D. from
University
of Washington (U.S.A.) in 2007. My research area is mainly in nonsmooth convex optimization. For more details, see
curriculum
vitae.

**My thesis advisor: **Professor
Paul Tseng.

**My Recent Research Papers **

M. Kang, S. Yun, and H. Woo, Two-level convex relaxed variational model for multiplicative denoising, December 2011, submitted to SIAM J. Imaging Sci.

H. Woo and S. Yun, Proximal linearized alternating direction method for multiplicative denoising, June 2011, submitted to SIAM J. Sci. Comput.

S. Yun and H. Woo, A new multiplicative denoising variational model based on m-th root transformation, IEEE Trans. on Image Processing, 21 (2012), 2523 -- 2533.

H. Woo and S. Yun, Alternating minimization algorithm for speckle reduction with shifting technique, IEEE Trans. on Image Processing 21 (2012), 1701 -- 1714. (ama-speckle.pdf)

S. Yun, P. Tseng, and K.-C. Toh, A Block Coordinate Gradient Descent Method for Regularized Convex Separable Optimization and Covariance Selection, Math. Prog. 129 (2011), 331 -- 355. (BCGD.pdf)

Z. Shen, K.-C. Toh, and S. Yun, An Accelerated Proximal Gradient Algorithm for Frame Based Image Restorations via the Balanced Approach, SIAM J. Imaging Sci. 4 (2011), 573 -- 596. (apgimage.pdf)

S. Yun and H. Woo, Linearized Proximal Alternating Minimization Algorithm for Motion Deblurring by Nonlocal Regularization, Pattern Recognition 44 (2011), 1312 -- 1326. (lpama.pdf)

S. Yun and K.-C. Toh, A Coordinate Gradient Descent Method for L1-regularized Convex Minimization, Comput. Optim. Appl. 48 (2011), 273 -- 307. (cgd_l1.pdf, matlab code of CGD method for L1-regularized least linear squares problem, matlab code of CGD method for L1-regularized logistic regression problem)

P. Tseng and S. Yun, A Coordinate Gradient Descent Method for Linearly Constrained Smooth Optimization and Support Vector Machines Training, Comput. Optim. Appl. 47 (2010), 179 -- 206 (svm.pdf)

K.-C. Toh and S. Yun, An Accelerated Proximal Gradient Algorithm for Nuclear Norm Regularized Least Squares Problems, Pacific J. Optim. 6 (2010), 615 -- 640 (mc.pdf, matlab code)

P. Tseng and S. Yun, Block-Coordinate Gradient Descent Method for Linearly Constrained Nonsmooth Separable Optimization, J. Optim. Theory Appl. 140 (2009), 513 -- 535. (cgd_cnobi.pdf)

P. Tseng and S. Yun, A Coordinate Gradient Descent Method for Nonsmooth Separable Minimization, Math. Prog. 117 (2009) 387 -- 423 (cgd.pdf, matlab codeof coordinate gradient descent (CGD) method for unconstrained optimization with l1-regularization)

**Recent Talks**

talk at KAIST, May 2012

talk at Yonsei University, April 2012

talk at CSE Seminar in Yonsei University, December 2011

talk at Medical Imaging Seminar in Yonsei University, November 2011

talk at Forum "Math-for-Industry" 2011, October 2011

talk at the KSIAM 2010 Annual Meeting, December 2010

talk at the 2010 Global KMS International Conference, October 2010

talk at the Ewha Womans University, April 2010

talk1, talk2 at the 2009 NIMS Thematic Winter School, December 2009

talk at the 2009 Workshop on Nonlinear analysis and Optimization, November 2009

talk at the Chungbuk National University and the Kyungpook National University, June 2009

talk at the Kyungpook National University, June 2009

talk at the Singapore-MIT Alliance 10th Anniversary Symposium, January 2009

talk at the INFORMS Annual Meeting, November 2007

talk at the Second Mathematical Programming Society International Conference on Continuous Optimization, August 2007

talk at the 19th International Symposium on Mathematical Programming, July 2006

talk at the eighth SIAM Conference on Optimization, May 2005

**Other sites **

The R Project for Statistical Computing