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 | 2470 | 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 | 979 | 2007 |
Trend Filtering SJ Kim, K Koh, S Boyd, D Gorinevsky SIAM review 51 (2), 339-360, 2009 | 942 | 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 | 166 | 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 |