Seung-Jean Kim

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Stephen BoydProfessor of Electrical Engineering, Computer Science, and Management Science, StanfordVerified email at stanford.edu
Michael (Miki) LustigProfessor of Electrical Engineering and Computer Science, UC BerkeleyVerified email at eecs.berkeley.edu
Dimitry GorinevskyConsulting Professor in Electrical Engineering, Stanford UniversityVerified email at stanford.edu
Almir MutapcicVerified email at alumni.stanford.edu
Mark HorowitzProfessor of Electrical Engineering and Computer ScienceVerified email at ee.stanford.edu
Lieven VandenbergheUCLAVerified email at ucla.edu
Lin XiaoFacebook AI ResearchVerified email at fb.com
John PaulyProfessor of Electrical Engineering, Stanford UniversityVerified email at stanford.edu
Jisung OhSamsung ElectronicsVerified email at samsung.com
Jungwon LeeVice President, Samsung US R&DVerified email at samsung.com
Zhi-Quan LuoProfessor, The Chinese University of Hong Kong, Shenzhen, ChinaVerified email at cuhk.edu.cn
Mario ParenteAssociate Professor of Electrical and Computer Engineering, University of Massachusetts AmherstVerified email at ecs.umass.edu
Xinlei WangProfessor of Statistics, Southern Methodist UniversityVerified email at smu.edu
Sungroh YoonProfessor, Electrical and Computer Engineering & Artificial Intelligence, Seoul National UniversityVerified email at snu.ac.kr
Ravi NarasimhanVerified email at stanfordalumni.org
Young-Han KimUniversity of California, San DiegoVerified email at ucsd.edu
Kyu S. HahnSeoul National UniversityVerified email at snu.ac.kr
John CioffiProfessor of EE, Stanford University

Seung-Jean Kim

Unknown affiliation

Verified email at sjklab.net

Large-Scale Optimization with Applications Dynamic Optimization Machine Learning Quantitative Finance Control.


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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	2449	2007
A tutorial on geometric programming S Boyd, SJ Kim, L Vandenberghe, A Hassibi Optimization and engineering 8 (1), 67-127, 2007	1246	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	1118	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	870	2007
Trend Filtering SJ Kim, K Koh, S Boyd, D Gorinevsky SIAM review 51 (2), 339-360, 2009	669	2009
Digital circuit optimization via geometric programming SP Boyd, SJ Kim, DD Patil, MA Horowitz Operations research 53 (6), 899-932, 2005	218	2005
A game-theoretic approach to power allocation in frequency-selective Gaussian interference channels ST Chung, SJ Kim, J Lee, JM Cioffi in Proc. IEEE International Symposium on Inform. Theory, Pacifico, 2003	218	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	190	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	136	2013
Robust fisher discriminant analysis SJ Kim, A Magnani, S Boyd Advances in neural information processing systems, 659-666, 2006	131	2006
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	122	2008
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	118	2008
l1_ls: A Matlab solver for large-scale l1-regularized least square problems K Koh http://www. stanford. edu/~ boyd/l1_ls, 2007	113*	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	88	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	86	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	82	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	80*	2005
Tractable approximate robust geometric programming KL Hsiung, SJ Kim, S Boyd Optimization and Engineering 9 (2), 95-118, 2008	67	2008
GGPLAB: a matlab toolbox for geometric programming A Mutapcic, K Koh, SJ Kim, S Boyd Available from www. st anford. edu/boyd/ggplab, 2006	55*	2006
A tractable method for robust downlink beamforming in wireless communications A Mutapcic, SJ Kim, S Boyd 2007 Conference Record of the Forty-First Asilomar Conference on Signals …, 2007	51	2007

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