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Kwangmoo Koh
Kwangmoo Koh
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Verificeret mail på alumni.stanford.edu
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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
24262007
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
9652007
Trend Filtering
SJ Kim, K Koh, S Boyd, D Gorinevsky
SIAM review 51 (2), 339-360, 2009
8992009
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
3362007
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
1492017
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
1002007
l1_ls: A Matlab solver for large-scale l1-regularized least square problems
K Koh
http://www. stanford. edu/~ boyd/l1_ls, 2007
672007
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
382006
A Method for large-scale l~ 1-regularized logistic regression
K Koh, SJ Kim, S Boyd
AAAI, 565-571, 2007
372007
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
182008
Ggplab version 1.00: a matlab toolbox for geometric programming
A Mutapcic, K Koh, S Kim, S Boyd
January, 2006
172006
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
72007
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
42007
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
12009
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
12007
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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Artikler 1–17