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 XiaoMeta AI, FAIR (Fundamental AI Research)Verified email at meta.com
John PaulyProfessor of Electrical Engineering, Stanford UniversityVerified email at stanford.edu
Jisung OhSamsung ElectronicsVerified email at samsung.com
Jungwon LeeExecutive Vice President, SamsungVerified 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 WangJenkins-Garrett Professor of Statistics and Data Science, University of Texas at ArlingtonVerified email at uta.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.


Title Sort by citations Sort by year Sort by 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	2826	2007
A tutorial on geometric programming S Boyd, SJ Kim, L Vandenberghe, A Hassibi Optimization and engineering 8, 67-127, 2007	1527	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	1289	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	985	2007
Trend Filtering SJ Kim, K Koh, S Boyd, D Gorinevsky SIAM review 51 (2), 339-360, 2009	955	2009
Digital circuit optimization via geometric programming SP Boyd, SJ Kim, DD Patil, MA Horowitz Operations research 53 (6), 899-932, 2005	238	2005
A game-theoretic approach to power allocation in frequency-selective Gaussian interference channels ST Chung, SJ Kim, J Lee, JM Cioffi IEEE International Symposium on Information Theory, 2003. Proceedings., 316-316, 2003	228	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	199	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	186	2013
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	170	2008
Robust fisher discriminant analysis SJ Kim, A Magnani, S Boyd Advances in neural information processing systems 18, 2005	166	2005
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	156	2008
l1_ls: A Matlab solver for large-scale l1-regularized least square problems K Koh http://www. stanford. edu/~ boyd/l1_ls, 2007	123*	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	103	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	97	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	93	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	82*	2005
Tractable approximate robust geometric programming KL Hsiung, SJ Kim, S Boyd Optimization and Engineering 9, 95-118, 2008	74	2008
Maximum likelihood covariance estimation with a condition number constraint JH Won, SJ Kim 2006 Fortieth Asilomar Conference on Signals, Systems and Computers, 1445-1449, 2006	58	2006
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

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