An Interior-Point Method for Large-Scale-Regularized Least Squares SJ Kim, K Koh, M Lustig, S Boyd, D Gorinevsky IEEE journal of selected topics in signal processing 1 (4), 606-617, 2007 | 2789 | 2007 |
A tutorial on geometric programming S Boyd, SJ Kim, L Vandenberghe, A Hassibi Optimization and engineering 8, 67-127, 2007 | 1499 | 2007 |
Distributed average consensus with least-mean-square deviation L Xiao, S Boyd, SJ Kim Journal of parallel and distributed computing 67 (1), 33-46, 2007 | 1272 | 2007 |
An interior-point method for large-scale l1-regularized logistic regression K Koh, SJ Kim, S Boyd Journal of Machine learning research 8 (Jul), 1519-1555, 2007 | 973 | 2007 |
Trend Filtering SJ Kim, K Koh, S Boyd, D Gorinevsky SIAM review 51 (2), 339-360, 2009 | 925 | 2009 |
Digital circuit optimization via geometric programming SP Boyd, SJ Kim, DD Patil, MA Horowitz Operations research 53 (6), 899-932, 2005 | 235 | 2005 |
A game-theoretic approach to power allocation in frequency-selective Gaussian interference channels ST Chung, SJ Kim, J Lee, JM Cioffi IEEE International Symposium on Information Theory, 2003. Proceedings., 316-316, 2003 | 226 | 2003 |
Optimal kernel selection in kernel fisher discriminant analysis SJ Kim, A Magnani, S Boyd Proceedings of the 23rd international conference on Machine learning, 465-472, 2006 | 199 | 2006 |
Condition-number-regularized covariance estimation JH Won, J Lim, SJ Kim, B Rajaratnam Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2013 | 182 | 2013 |
Robust fisher discriminant analysis SJ Kim, A Magnani, S Boyd Advances in neural information processing systems 18, 2005 | 163 | 2005 |
A fast method for designing time-optimal gradient waveforms for arbitrary k-space trajectories M Lustig, SJ Kim, JM Pauly IEEE transactions on medical imaging 27 (6), 866-873, 2008 | 160 | 2008 |
Robust beamforming via worst-case SINR maximization SJ Kim, A Magnani, A Mutapcic, SP Boyd, ZQ Luo IEEE Transactions on Signal Processing 56 (4), 1539-1547, 2008 | 150 | 2008 |
l1_ls: A Matlab solver for large-scale l1-regularized least square problems K Koh http://www. stanford. edu/~ boyd/l1_ls, 2007 | 122* | 2007 |
An efficient method for compressed sensing SJ Kim, K Koh, M Lustig, S Boyd 2007 IEEE International Conference on Image Processing 3, III-117-III-120, 2007 | 101 | 2007 |
Hyperspectral image unmixing via alternating projected subgradients A Zymnis, SJ Kim, J Skaf, M Parente, S Boyd 2007 Conference Record of the Forty-First Asilomar Conference on Signals …, 2007 | 97 | 2007 |
A minimax theorem with applications to machine learning, signal processing, and finance SJ Kim, S Boyd SIAM Journal on Optimization 19 (3), 1344-1367, 2008 | 91 | 2008 |
A new method for design of robust digital circuits D Patil, S Yun, SJ Kim, A Cheung, M Horowitz, S Boyd Sixth international symposium on quality electronic design (isqed'05), 676-681, 2005 | 82* | 2005 |
Tractable approximate robust geometric programming KL Hsiung, SJ Kim, S Boyd Optimization and Engineering 9, 95-118, 2008 | 74 | 2008 |
Maximum likelihood covariance estimation with a condition number constraint JH Won, SJ Kim 2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 1445-1449, 2006 | 57 | 2006 |
GGPLAB: a matlab toolbox for geometric programming A Mutapcic, K Koh, SJ Kim, S Boyd Available from www. st anford. edu/boyd/ggplab, 2006 | 54* | 2006 |