Martin S. Andersen

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Lieven VandenbergheUCLAVerified email at ucla.edu
Anders HanssonProfessor in Automatic Control, Linkoping UniversityVerified email at liu.se
Tianshi CHENProfessor, The Chinese University of Hong Kong, Shenzhen, ChinaVerified email at cuhk.edu.cn
Sina Khoshfetrat PakazadVice President of Data ScienceVerified email at c3.ai
Anders RantzerProfessor, Lund UniversityVerified email at control.lth.se
Lennart LjungProfessor of Automatic Control, Linköping University, SwedenVerified email at isy.liu.se
Alessandro ChiusoProfessor of Automatic Control, University of PadovaVerified email at dei.unipd.it
Gianluigi PillonettoProfessor of Automatic Control, University of PadovaVerified email at dei.unipd.it
Emil SidkyUniversity of ChicagoVerified email at uchicago.edu
Sean RoseAssistant Professor, University of Texas Health Science Center at Houston McGovern Medical SchoolVerified email at uth.tmc.edu
Per Christian HansenProfessor of Scientific Computing, Technical University of DenmarkVerified email at dtu.dk
Jakob Sauer JørgensenSenior Researcher, Technical University of Denmark (DTU), DenmarkVerified email at dtu.dk
Yiqiu DongTechnical University of DenmarkVerified email at dtu.dk
Zhang LiuFacebookVerified email at fb.com
Yifan SunAssistant Prof at Stonybrook CS DeptVerified email at stonybrook.edu
Oscar BorriesTICRAVerified email at ticra.com
Efren Fernandez-GrandeAssociate Professor, Technical University of DenmarkVerified email at elektro.dtu.dk
Oliver LylloffResearcher at Wind Energy Dept., Technical University of DenmarkVerified email at dtu.dk
Peter D LeeRoyal Academy of Engineering Chair in Emerging Technologies, University College LondonVerified email at ucl.ac.uk
Daniil Kazantsevsenior software scientistVerified email at diamond.ac.uk

Martin S. Andersen

Technical University of Denmark

Verified email at dtu.dk - Homepage

Optimization Numerical Methods Scientific Computing


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CVXOPT: Python software for convex optimization M Andersen, J Dahl, L Vandenberghe	373*	2013
Chordal graphs and semidefinite optimization L Vandenberghe, MS Andersen Foundations and Trends® in Optimization 1 (4), 241-433, 2015	304	2015
System identification via sparse multiple kernel-based regularization using sequential convex optimization techniques T Chen, MS Andersen, L Ljung, A Chiuso, G Pillonetto IEEE, 2014	195	2014
Interior-Point Methods for Large-Scale Cone Programming M Andersen, J Dahl, Z Liu, L Vandenberghe Optimization for Machine Learning, 55-83, 2011	173	2011
Reduced-complexity semidefinite relaxations of optimal power flow problems MS Andersen, A Hansson, L Vandenberghe IEEE Transactions on Power Systems 29 (4), 1855-1863, 2013	97	2013
Implementation of nonsymmetric interior-point methods for linear optimization over sparse matrix cones MS Andersen, J Dahl, L Vandenberghe Mathematical Programming Computation 2 (3), 167-201, 2010	89	2010
Robust Stability Analysis of Sparsely Interconnected Uncertain Systems MS Andersen, SK Pakazad, A Hansson, A Rantzer arXiv preprint arXiv:1311.2602, 2013	81	2013
Improving the efficiency of deconvolution algorithms for sound source localization O Lylloff, E Fernández-Grande, F Agerkvist, J Hald, ET Roig, ... The Journal of the Acoustical Society of America 138 (1), 172-180, 2015	73	2015
Decomposition in conic optimization with partially separable structure Y Sun, MS Andersen, L Vandenberghe SIAM Journal on Optimization 24 (2), 873-897, 2014	68	2014
Distributed primal–dual interior-point methods for solving tree-structured coupled convex problems using message-passing S Khoshfetrat Pakazad, A Hansson, MS Andersen, I Nielsen Optimization Methods and Software 32 (3), 401-435, 2017	64	2017
Joint image reconstruction method with correlative multi-channel prior for x-ray spectral computed tomography D Kazantsev, JS Jørgensen, MS Andersen, WRB Lionheart, PD Lee, ... Inverse Problems 34 (6), 064001, 2018	62	2018
Generalized row-action methods for tomographic imaging MS Andersen, PC Hansen Numerical Algorithms 67 (1), 121-144, 2014	42	2014
On the robustness and scalability of semidefinite relaxation for optimal power flow problems A Eltved, J Dahl, MS Andersen Optimization and Engineering 21 (2), 375-392, 2020	41	2020
Distributed semidefinite programming with application to large-scale system analysis SK Pakazad, A Hansson, MS Andersen, A Rantzer IEEE Transactions on Automatic Control, 2017	41	2017
CVXOPT: Convex Optimization M Andersen, J Dahl, L Vandenberghe Astrophysics Source Code Library, ascl: 2008.017, 2020	37	2020
Logarithmic barriers for sparse matrix cones MS Andersen, J Dahl, L Vandenberghe Optimization Methods and Software 28 (3), 396-423, 2013	34	2013
Noise properties of CT images reconstructed by use of constrained total-variation, data-discrepancy minimization S Rose, MS Andersen, EY Sidky, X Pan Medical Physics 42 (5), 2690-2698, 2015	33	2015
CVXOPT M Andersen, J Dahl, L Vandenberghe	30	2012
Inexact proximal Newton methods for self-concordant functions J Li, MS Andersen, L Vandenberghe Mathematical Methods of Operations Research 85, 19-41, 2017	28	2017
CVXOPT: Python software for convex optimization, version 1.1 M Andersen, J Dahl, L Vandenberghe URL https://cvxopt. org, 2015	22	2015

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