Kwangmoo Koh
Kwangmoo Koh
Unknown affiliation
Verified email at alumni.stanford.edu
Title
Cited by
Cited by
Year
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
19992007
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
7732007
Trend Filtering
SJ Kim, K Koh, S Boyd, D Gorinevsky
SIAM review 51 (2), 339-360, 2009
5772009
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
3172007
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
842007
l1_ls: A Matlab solver for large-scale l1-regularized least square problems
K Koh
http://www. stanford. edu/~ boyd/l1_ls, 2007
662007
Multi-period trading via convex optimization
S Boyd, E Busseti, S Diamond, RN Kahn, K Koh, P Nystrup, J Speth
arXiv preprint arXiv:1705.00109, 2017
572017
An interior-point method for large-scale ℓ1-regularized logistic regression
S Kim, K Koh, M Lustig, S Boyd, D Gorinevsky
Journal of Machine learning research, 2007
362007
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
312006
A Method for Large-Scale l~ 1-Regularized Logistic Regression
K Koh, SJ Kim, S Boyd
AAAI, 565-571, 2007
272007
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
152008
GGPLAB version 1.00: A matlab toolbox for geometric programming
A Mutapcic, K Koh, S Kim, S Boyd
January, 2006
132006
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
62007
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
22009
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
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Articles 1–16