Sunyoung Kim is a professor of mathematics at Ewha. She received a Ph. D. from State University of New York at Stony Brook.
Her research interests include algorithms for quadratic, semidefinite, copositive programming, polynomial optimization, and the Euclidean distance matrix problem. One recent result of her work has been to develop a unified framework for polynomial optimization problems via Lagrangian-conic relaxation method, and algorithms.
Kim has been teaching Numerical Analysis, Numerical Differential Equations, Linear Algebra, Applied Mathematics, and Optimization.
Doubly nonnegative relaxations are equivalent to completely positive reformulations of quadratic optimization problems with block-clique graph structuresJournal of Global Optimization, 2020, v.77 no.3, 513-541
On the conditions for the finite termination of ADMM and its applications to SOS polynomials feasibility problemsComputational Optimization and Applications, 2019, v.74 no.2, 317-344
Solving pooling problems with time discretization by LP and SOCP relaxations and rescheduling methodsJournal of Global Optimization, 2019, v.75 no.3, 631-654
Equivalences and differences in conic relaxations of combinatorial quadratic optimization problemsJOURNAL OF GLOBAL OPTIMIZATION, 2018, v.72 no.4, 619-653
LAGRANGIAN-CONIC RELAXATIONS, PART I: A UNIFIED FRAMEWORK AND ITS APPLICATIONS TO QUADRATIC OPTIMIZATION PROBLEMSPACIFIC JOURNAL OF OPTIMIZATION, 2018, v.14 no.1, 161-192
EXACT SEMIDEFINITE PROGRAMMING RELAXATIONS WITH TRUNCATED MOMENT MATRIX FOR BINARY POLYNOMIAL OPTIMIZATION PROBLEMSSIAM JOURNAL ON OPTIMIZATION, 2017, v.27 no.1, 565-582
A Lagrangian–DNN relaxation: a fast method for computing tight lower bounds for a class of quadratic optimization problemsMathematical Programming, 2016, v.156 no.42371
Semidefinite programming relaxation methods for global optimization problems with sparse polynomials and unbounded semialgebraic feasible setsJournal of Global Optimization, 2016, v.65 no.2
Extension of Completely Positive Cone Relaxation to Moment Cone Relaxation for Polynomial OptimizationJournal of Optimization Theory and Applications, 2015, 13 Aug 2015
SIMPLIFIED COPOSITIVE AND LAGRANGIAN RELAXATIONS FOR LINEARLY CONSTRAINED QUADRATIC OPTIMIZATION PROBLEMS IN CONTINUOUS AND BINARY VARIABLESPACIFIC JOURNAL OF OPTIMIZATION, 2014, v.10 no.3 SI., 437-451
A QUADRATICALLY CONSTRAINED QUADRATIC OPTIMIZATION MODEL FOR COMPLETELY POSITIVE CONE PROGRAMMINGSIAM JOURNAL ON OPTIMIZATION, 2013, v.23 no.4, 2320-2340
Algorithm 920: SFSDP: A sparse version of full semidefinite programming relaxation for sensor network localization problemsACM Transactions on Mathematical Software, 2012, v.38 no.4
Exploiting sparsity in SDP relaxation of polynomial optimization problemsInternational Series in Operations Research and Management Science, 2012, v.166, 499-531
Exploiting sparsity in linear and nonlinear matrix inequalities via positive semidefinite matrix completionMathematical Programming, 2011, v.129 no.1, 33-68
[학술지논문] A Newton-bracketing method for a simple conic optimization problem
OPTIMIZATION METHODS & SOFTWARE, 2021, v.36
no.2-3
, 371-388
SCIE
[학술지논문] A GEOMETRICAL ANALYSIS ON CONVEX CONIC REFORMULATIONS OF QUADRATIC AND POLYNOMIAL OPTIMIZATION PROBLEMS
SIAM JOURNAL ON OPTIMIZATION, 2020, v.30
no.2
, 1251-1273
SCI
[학술지논문] A dual spectral projected gradient method for log-determinant semidefinite problems
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 2020, v.76
no.1
, 33-68
SCI
[학술지논문] Doubly nonnegative relaxations are equivalent to completely positive reformulations of quadratic optimization problems with block-clique graph structures
JOURNAL OF GLOBAL OPTIMIZATION, 2020, v.77
no.3
, 513-541
SCI
[학술지논문] Algorithm 996: BBCPOP: A Sparse Doubly Nonnegative Relaxation of Polynomial Optimization Problems With Binary, Box, and Complementarity Constraints
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 2019, v.45
no.3
, 34-34
SCI
[학술지논문] LAGRANGIAN-CONIC RELAXATIONS, PART II: APPLICATIONS TO POLYNOMIAL OPTIMIZATION PROBLEMS
PACIFIC JOURNAL OF OPTIMIZATION, 2019, v.15
no.3
, 415-439
SCIE
[학술지논문] On the conditions for the finite termination of ADMM and its applications to SOS polynomials feasibility problems
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 2019, v.74
no.2
, 317-344
SCI
[학술지논문] Solving pooling problems with time discretization by LP and SOCP relaxations and rescheduling methods
JOURNAL OF GLOBAL OPTIMIZATION, 2019, v.75
no.3
, 631-654
SCI
[학술지논문] Equivalences and differences in conic relaxations of combinatorial quadratic optimization problems
JOURNAL OF GLOBAL OPTIMIZATION, 2018, v.72
no.4
, 619-653
SCI
[학술지논문] LAGRANGIAN-CONIC RELAXATIONS, PART I: A UNIFIED FRAMEWORK AND ITS APPLICATIONS TO QUADRATIC OPTIMIZATION PROBLEMS
PACIFIC JOURNAL OF OPTIMIZATION, 2018, v.14
no.1
, 161-192
SCIE
[학술지논문] A robust Lagrangian-DNN method for a class of quadratic optimization problems
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 2017, v.66
no.3
, 453-479
SCI
[학술지논문] Binary quadratic optimization problems that are difficult to solve by conic relaxations
DISCRETE OPTIMIZATION, 2017, v.24
no.Special SI
, 170-183
SCIE
[학술지논문] EXACT SEMIDEFINITE PROGRAMMING RELAXATIONS WITH TRUNCATED MOMENT MATRIX FOR BINARY POLYNOMIAL OPTIMIZATION PROBLEMS
SIAM JOURNAL ON OPTIMIZATION, 2017, v.27
no.1
, 565-582
SCI
[학술지논문] A Lagrangian-DNN relaxation: a fast method for computing tight lower bounds for a class of quadratic optimization problems
MATHEMATICAL PROGRAMMING, 2016, v.156
no.1-2
, 161-187
SCI
[학술지논문] Extension of Completely Positive Cone Relaxation to Moment Cone Relaxation for Polynomial Optimization
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, 2016, v.168
no.3
, 884-900
SCI
[학술지논문] Semidefinite programming relaxation methods for global optimization problems with sparse polynomials and unbounded semialgebraic feasible sets
JOURNAL OF GLOBAL OPTIMIZATION, 2016, v.65
no.2
, 175-190
SCI
[학술지논문] SIMPLIFIED COPOSITIVE AND LAGRANGIAN RELAXATIONS FOR LINEARLY CONSTRAINED QUADRATIC OPTIMIZATION PROBLEMS IN CONTINUOUS AND BINARY VARIABLES
PACIFIC JOURNAL OF OPTIMIZATION, 2014, v.10
no.3
, 437-451
SCIE
[학술지논문] A CONTINUATION METHOD FOR LARGE-SIZED SENSOR NETWORK LOCALIZATION PROBLEMS
PACIFIC JOURNAL OF OPTIMIZATION, 2013, v.9
no.0
, 117-136
SCI
[학술지논문] A QUADRATICALLY CONSTRAINED QUADRATIC OPTIMIZATION MODEL FOR COMPLETELY POSITIVE CONE PROGRAMMING
SIAM JOURNAL ON OPTIMIZATION, 2013, v.23
no.4
, 2320-2340
SCI
[학술지논문] Algorithm 920: SFSDP: A Sparse Version of Full Semidefinite Programming Relaxation for Sensor Network Localization Problems
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 2012, v.38
no.4
, 1-1
SCI
[학술지논문] EXPLOITING SPARSITY IN SDP RELAXATION FOR SENSOR NETWORK LOCALIZATION
SIAM JOURNAL ON OPTIMIZATION, 2009, v.20
, 192-215
[학술지논문] SPARSE SECOND ORDER CONE PROGRAMMING FORMULATIONS FOR CONVEX OPTIMIZATION PROBLEMS
JOURNAL OF THE OPERATIONS RESEARCH SOCIETY OF JAPAN, 2008, v.51
no.3
, 241-264
SCIE
[학술지논문] SparsePOP - A sparse semidefinite programming relaxation of polynomial optimization problems
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 2008, v.35
no.2
, 121-134
SCI
[학술발표] SDP and DNN relaxations of discrete polynomial optimization problemsICCOPT 2016, 일본, Tokyo, 2016-08-10
ICCOPT 2016, 2016
Exact SDP relaxations for quadratic programs with bipartite graph structuresJournal of Global Optimization, 2023, v.86 no.3, 671-691
Doubly nonnegative relaxations for quadratic and polynomial optimization problems with binary and box constraintsMathematical Programming, 2022, v.193 no.2, 761-787
A GEOMETRICAL ANALYSIS ON CONVEX CONIC REFORMULATIONS OF QUADRATIC AND POLYNOMIAL OPTIMIZATION PROBLEMSSIAM JOURNAL ON OPTIMIZATION, 2020, v.30 no.2, 1251-1273
[학술지논문] Further development in convex conic reformulation of geometric nonconvex conic optimization problems
SIAM JOURNAL ON OPTIMIZATION, 2024, v...
no..
, .-.
SCIE
[학술지논문] T-semidefinite programming relaxation with third-order tensors for constrained polynomial optimization
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, 2024, v...
no..
, ..-.
SCIE
[학술지논문] Exact SDP relaxations for quadratic programs with bipartite graph structures
JOURNAL OF GLOBAL OPTIMIZATION, 2023, v.86
no.3
, 671-691
SCIE
[학술지논문] Strong duality of a conic optimization problem with a single hyperplane and two cone constraints
OPTIMIZATION, 2023, v.2023
no.0
, 2251987-2251987
SCIE
[학술지논문] Doubly nonnegative relaxations for quadratic and polynomial optimization problems with binary and box constraints
MATHEMATICAL PROGRAMMING, 2022, v.193
no.2
, 761-787
SCI
[학술지논문] Exact SDP relaxations of quadratically constrained quadratic programs with forest structures
JOURNAL OF GLOBAL OPTIMIZATION, 2022, v.82
no.2
, 243-262
SCI
[학술발표] Convex conic reformulation of geometric nonconvex conic optimization problems and exact solutions of QCQPs by semidefinite relaxationsISMP (Internatioanl Symposium on Mathematical Programming) 2024, 캐나다, Montreal, 2024-07-26
Proceeding of ISMP, 2024, .-.
[학술발표] High-rank Solution of Sum-of-Squares Relaxations for Exact Matrix CompletionISMP(International Symposium on Mathematical Programming) 2024, 캐나다, Montreal, 2024-07-26
ISMP Proceeding, 2024
[학술발표] Solving Large-Scale Quadratic Assignment Problems by a Parallelized Lagrangian-DNN-Based Branch-and-BoundISMP(International Symposium on Mathematical Programming) 2024, 캐나다, Montreal, 2024-07-24
ISMP Proceeding, 2024
[학술발표] Convex Conic Reformulations of Geometric Nonconvex Conic Optimization Problems for a Class of Quadratic Optimization ProblemsSIAM Optimizaiton Meeting 2023, 미국, Seattle, 2023-06-01
SIAM Society Proceeding, 2023, 95-95
[학술발표] Equivalent Sufficient Conditions for Exact SDP Relaxation and the Saddle Point of Lagrangian Function of QCQPICIAM 2023, 일본, Tokyo, 2023-08-23
Proceedings of ICIAM 2023, 2023
[학술발표] Tight Semidefinite Relaxations for Sign-Indefinite Qcqps with Bipartite StructuresSIAM Optimizaiton Meeting 2023, 미국, Seattle, 2023-06-01
SIAM Society Proceeding, 2023, 94-94
[학술발표] Tightness conditions of SDP relaxation for QCQPs with bipartite graph structureICIAM 2023, 일본, Tokyo, 2023-08-23
Proceedings of ICIAM 2023, 2023, .-.
[학술발표] Exact conic relaxations for quadratic optimization problemsInternational Workshop on Continuous Optimization, 일본, Tokyo, 2022-12-03
International Workshop on Continuous Optimization 2022, 2022, 10-10
[학술발표] A Newton-Bracketing Method for Quadratic and Polynomial Optimization ProblemsSIAM Optimization 2021, 미국, 2021-07-22
SIAM Proceeding, 2021, 287-287
[학술발표] Doubly nonnegative Relaxations and Completely Positive Reformulations of Quadratic Optimization Problems with Block-Clique StructuresThe 2nd Greater Bay Area Worship on Computational Optimization, 홍콩, Hong Kong, 2021-12-11
Greater Bay Area Worship on Computational Optimization, 2021
[학술발표] Efficient SOCP Relaxations for Pooling ProblemsSIAM Optimization 2021, 미국, 2021-07-23
SIAM proceeding, 2021, 309-309
[학술발표] Exact semidefinite relaxations for QCQPs with forest- structured matrices and its applicationsIFORS 2021 , 대한민국, online, 2021-08-24
IFORS 2021 , 2021, 15-15
[학술발표] Exactness Conditions for Semidefinite Relaxation of Nonconvex QCQPS with Forest Structures
SIAM Optimization 2021, 미국, 2021-07-23
SIAM Opt proceeding, 2021, 309-309
[학술발표] A dual spectral projected gradient method for log-determinant semidefinite problemsICCOPT 2019, 독일, 베를린, 2019-08-06
ICCOPT 2019, 2019
[학술발표] Doubly nonnegative programs equivalent to completely positive reformulations of quadratic optimization problems with block clique structuresICCOPT 2019, 독일, 베를린, 2019-08-06
ICCOPT 2019, 2019
[학술발표] BBCPOP: a Matlab package for sparse DNN relaxations of polynomial optimization problems with binary, box and complementarity conditionsInternational Symposium on Mathematical Programming (ISMP2018), 프랑스, 보르드, 2018-07-03
Proceedings, 2018
[학술발표] Solving a convergent hierarchy of DNN relaxations of polynomial optimization problems
with the Newton bracketing methodICPTO 2018 (International conference on polynomial and tensor optimization), 중국, XiangTan, 2018-12-20
Proceeding of ICPTO2018, 2018, 12-13
[학술발표] A robust Lagrangian-DNN method for a class of quadratic optimization problemsICCOPT 2016, 일본, 2016-08-10
Proceeding of ICCOPT 2016 , 2016
[학술발표] A numerical study on the sum-of-squares relaxation for a Lagrangian relaxation of
quadratic optimization problems with binary variablesISMP 2015 (International Symposium on Mathematical Programming), 미국, Pittsburg, 2015-07-16
ISMP 2015, 2015
[학술발표] A quadratic optimization model for completely positive programming and its application to 0-1 mixed integer linearly constrained quadratic optimization problemsICCOPT 2013, 포르투갈, lisbon, 2013-08-01
Proceeding of ICCOPT 2013, 2013
[학술발표] Extension of completely positive cone relaxation to polynomial optimizationICCOPT 2013 (International Conference on Continuous Optimization), 포르투갈, 리스본, 2013-08-01
Proceeding, 2013
[학술발표] A Successive SDP Relaxation Method for Distance Geometry ProblemsISMP 2012 (International Symposium on Mathematical Programming, 독일, Berlin, 2012-08-20
ISMP, 2012
[학술발표] Exploiting sparsity in SDP relaxation for sensor network localizationInternational Sym. on Math. Programming (ISMP) 2009, 미국, Chicago, 2009-08-27
ISMP 2009, 2009, 99-99
[학술발표] Semidefinite programmging approach for polynomial least squares problemsSIAM Optimization 2008, 미국, Boston, 2008-05-11
SIAM Optimization Meeting 2008, 2008
[학술발표] Solving polynomial least squares problems via semidefinite programming relaxationRIMS Workshop on Optimization, Kyoto University, 일본, kyoto, 2007-07-19
[학술발표] SparsePOP: a Sparse Semidefinite Programming Relaxation of Polynomial Optimization ProblemsOptimization and control (IMA), 미국, Minnesota, 2007-01-15