An Interior-Point Method for Large-Scale SJ Kim, K Koh, M Lustig, S Boyd, D Gorinevsky
IEEE journal of selected topics in signal processing 1 (4), 606-617, 2007
2474 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
980 2007 SJ Kim, K Koh, S Boyd, D Gorinevsky
SIAM review 51 (2), 339-360, 2009
945 2009 A method for large-scale l1-regularized least squares SJ Kim, K Koh, M Lustig, S Boyd, D Gorinevsky
IEEE Journal on Selected Topics in Signal Processing 1 (4), 606-617, 2007
337 2007 Multi-period trading via convex optimization S Boyd, E Busseti, S Diamond, RN Kahn, K Koh, P Nystrup, J Speth
Foundations and Trends® in Optimization 3 (1), 1-76, 2017
168 2017 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
102 2007 l1_ls: A Matlab solver for large-scale l1-regularized least square problems K Koh
http://www. stanford. edu/~ boyd/l1_ls, 2007
70 2007 A Method for large-scale l~ 1-regularized logistic regression K Koh, SJ Kim, S Boyd
AAAI, 565-571, 2007
39 2007 GGPLAB: a simple Matlab toolbox for geometric programming A Mutapcic, K Koh, S Kim, L Vandenberghe, S Boyd
web page and software: http://stanford. edu/boyd/ggplab, 2006
37 2006 Ggplab version 1.00: a matlab toolbox for geometric programming A Mutapcic, K Koh, S Kim, S Boyd
January, 2006
17 2006 Learning the kernel via convex optimization SJ Kim, A Zymnis, A Magnani, K Koh, S Boyd
2008 IEEE International Conference on Acoustics, Speech and Signal …, 2008
16 2008 An Efficient Method for Large-Scale l1 -Regularized Convex Loss Minimization K Koh, SJ Kim, S Boyd
2007 Information Theory and Applications Workshop, 223-230, 2007
6 2007 An Interior-Point Method for Large-scale L1-Regularized Least-square Prombles with Applications in Signal Processing and Statistics SJ Kim, K Koh, M Lustig
Journal of Machine Learning Research 7 (8), 1, 2007
4 2007 l1_logreg: A large-scale solver for l1-regularized logistic regression problems K Koh, SJ Kim, S Boyd
URL: http://www. stanford. edu/~ boyd/l1_logreg/(last retrieved on June 30 …, 2009
1 2009 An introduction to compressive sampling SJ Kim, K Koh, M Lustig, S Boyd, D Gorinevsky
IEEE Journal of Selected Topics in Signal Processing 1 (4), 606-617, 2007
1 2007 SPS Members Recognized with Awards SJ Kim, K Koh, M Lustig, S Boyd, T Virtanen, M Sound, ...
IEEE Signal Processing Magazine, 2013
2013 Methods for large-scale convex optimization problems with l1 regularization K Koh
Stanford University, 2009
2009 