By Professor Guoyin Li

Book Chapters

Li G; Wu H, 2023, 'Splitting Methods for Nonconvex and Nonsmooth Optimization', in Encyclopedia of Optimization, Springer International Publishing, pp. 1 - 19, http://dx.doi.org/10.1007/978-3-030-54621-2_847-1

Jeyakumar V; Lee G; Li G, 2010, 'Global Optimality Conditions for Classes of Non-convexMulti-objective Quadratic Optimization Problems', in Burachik RS; Yao J-C (ed.), Springer Optimization and Its Applications, Vol 47, Springer, pp. 177 - 186

Journal articles

Wang Q; Li J; Gao W; Li G; Liu X; Bradford MA, 2024, 'Smoothing and approximation of grassland fire loading data for engineering structures by Capped Extended Support Vector Regression', Engineering Structures, 319, http://dx.doi.org/10.1016/j.engstruct.2024.118848

Zeng L; Zhang Y; Li G; Pong TK; Wang X, 2024, 'Frank–Wolfe-type methods for a class of nonconvex inequality-constrained problems', Mathematical Programming, 208, pp. 717 - 761, http://dx.doi.org/10.1007/s10107-023-02055-y

Goberna MA; Jeyakumar V; Li G, 2024, 'The Stability of Robustness for Conic Linear Programs with Uncertain Data', Journal of Optimization Theory and Applications, 203, pp. 1509 - 1530, http://dx.doi.org/10.1007/s10957-024-02492-5

Zhao L; Li G; Penev S, 2024, 'Regularized distributionally robust optimization with application to the index tracking problem', Annals of Operations Research, 337, pp. 397 - 424, http://dx.doi.org/10.1007/s10479-023-05726-3

Wang Q; Wu D; Li G; Liu Z; Tong J; Chen X; Gao W, 2024, 'Machine learning aided uncertainty quantification for engineering structures involving material-geometric randomness and data imperfection', Computer Methods in Applied Mechanics and Engineering, 423, http://dx.doi.org/10.1016/j.cma.2024.116868

Jeyakumar V; Li G; Woolnough D; Wu H, 2024, 'Affinely adjustable robust optimization for radiation therapy under evolving data uncertainty via semi-definite programming', Optimization, 73, pp. 1807 - 1832, http://dx.doi.org/10.1080/02331934.2023.2178848

Huang QY; Jeyakumar V; Li G, 2024, 'Piecewise SOS-convex moment optimization and applications via exact semi-definite programs', EURO Journal on Computational Optimization, 12, http://dx.doi.org/10.1016/j.ejco.2024.100094

Pham TN; Dao MN; Shah R; Sultanova N; Li G; Islam S, 2023, 'A proximal subgradient algorithm with extrapolation for structured nonconvex nonsmooth problems', Numerical Algorithms, 94, pp. 1763 - 1795, http://dx.doi.org/10.1007/s11075-023-01554-5

Zhang Y; Li G; Pong TK; Xu S, 2023, 'Retraction-based first-order feasible methods for difference-of-convex programs with smooth inequality and simple geometric constraints', Advances in Computational Mathematics, 49, http://dx.doi.org/10.1007/s10444-022-10002-2

BOc RIT; Dao MN; Li G, 2023, 'INERTIAL PROXIMAL BLOCK COORDINATE METHOD FOR A CLASS OF NONSMOOTH SUM-OF-RATIOS OPTIMIZATION PROBLEMS', SIAM Journal on Optimization, 33, pp. 361 - 393, http://dx.doi.org/10.1137/22M1472000

Jeyakumar V; Lee JH; Lee GM; Li G; Woolnough D, 2022, 'Sums of Squares Polynomial Program Reformulations for Adjustable Robust Linear Optimization Problems with Separable Polynomial Decision Rules', Set-Valued and Variational Analysis, 30, pp. 1363 - 1380, http://dx.doi.org/10.1007/s11228-022-00648-x

Bot RI; Dao MN; Li G, 2022, 'Extrapolated Proximal Subgradient Algorithms for Nonconvex and Nonsmooth Fractional Programs', Mathematics of Operations Research, 47, pp. 2415 - 2443, http://dx.doi.org/10.1287/moor.2021.1214

Yu P; Li G; Pong TK, 2022, 'Kurdyka–Łojasiewicz Exponent via Inf-projection', Foundations of Computational Mathematics, 22, pp. 1171 - 1217, http://dx.doi.org/10.1007/s10208-021-09528-6

Wang Q; Feng Y; Wu D; Li G; Liu Z; Gao W, 2022, 'Polymorphic uncertainty quantification for engineering structures via a hyperplane modelling technique', Computer Methods in Applied Mechanics and Engineering, 398, http://dx.doi.org/10.1016/j.cma.2022.115250

Bello-Cruz Y; Li G; Nghia TTA, 2022, 'Quadratic Growth Conditions and Uniqueness of Optimal Solution to Lasso', Journal of Optimization Theory and Applications, 194, pp. 167 - 190, http://dx.doi.org/10.1007/s10957-022-02013-2

Woolnough D; Jeyakumar N; Li G; Loy CT; Jeyakumar V, 2022, 'Robust Optimization and Data Classification for Characterization of Huntington Disease Onset via Duality Methods', Journal of Optimization Theory and Applications, 193, pp. 649 - 675, http://dx.doi.org/10.1007/s10957-021-01835-w

Goberna MA; Jeyakumar V; Li G; Vicente-Pérez J, 2022, 'The radius of robust feasibility of uncertain mathematical programs: A Survey and recent developments', European Journal of Operational Research, 296, pp. 749 - 763, http://dx.doi.org/10.1016/j.ejor.2021.04.035

Chuong TD; Jeyakumar V; Li G; Woolnough D, 2022, 'Exact dual semi-definite programs for affinely adjustable robust SOS-convex polynomial optimization problems', Optimization, 71, pp. 3539 - 3569, http://dx.doi.org/10.1080/02331934.2021.1902521

Wang Q; Feng Y; Wu D; Yang C; Yu Y; Li G; Beer M; Gao W, 2022, 'Polyphase uncertainty analysis through virtual modelling technique', Mechanical Systems and Signal Processing, 162, http://dx.doi.org/10.1016/j.ymssp.2021.108013

Wang Q; Wu D; Li G; Gao W, 2021, 'A virtual model architecture for engineering structures with Twin Extended Support Vector Regression (T-X-SVR) method', Computer Methods in Applied Mechanics and Engineering, 386, http://dx.doi.org/10.1016/j.cma.2021.114121

Hu S; Li G, 2021, 'B -subdifferentials of the projection onto the matrix simplex', Computational Optimization and Applications, 80, pp. 915 - 941, http://dx.doi.org/10.1007/s10589-021-00316-0

Chuong TD; Jeyakumar V; Li G; Woolnough D, 2021, 'Exact SDP reformulations of adjustable robust linear programs with box uncertainties under separable quadratic decision rules via SOS representations of non-negativity', Journal of Global Optimization, 81, pp. 1095 - 1117, http://dx.doi.org/10.1007/s10898-021-01050-x

Goberna MA; Jeyakumar V; Li G, 2021, 'Calculating Radius of Robust Feasibility of Uncertain Linear Conic Programs via Semi-definite Programs', Journal of Optimization Theory and Applications, 189, pp. 597 - 622, http://dx.doi.org/10.1007/s10957-021-01846-7

Woolnough D; Jeyakumar V; Li G, 2021, 'Exact conic programming reformulations of two-stage adjustable robust linear programs with new quadratic decision rules', Optimization Letters, 15, pp. 25 - 44, http://dx.doi.org/10.1007/s11590-020-01595-y

Bello-Cruz Y; Li G; Nghia TTA, 2021, 'On the Linear Convergence of Forward–Backward Splitting Method: Part I—Convergence Analysis', Journal of Optimization Theory and Applications, 188, pp. 378 - 401, http://dx.doi.org/10.1007/s10957-020-01787-7

Jeyakumar V; Li G; Woolnough D, 2021, 'Quadratically adjustable robust linear optimization with inexact data via generalized S-lemma: Exact second-order cone program reformulations', EURO Journal on Computational Optimization, 9, http://dx.doi.org/10.1016/j.ejco.2021.100019

Chieu NH; Jeyakumar V; Li G, 2020, 'Convexifiability of continuous and discrete nonnegative quadratic programs for gap-free duality', EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 280, pp. 441 - 452, http://dx.doi.org/10.1016/j.ejor.2019.08.009

Burachik RS; Li G, 2020, 'Introduction', Springer Proceedings in Mathematics and Statistics, 313, pp. 3 - 5, http://dx.doi.org/10.1007/978-3-030-36568-4_1

Chuong TD; Jeyakumar V; Li G, 2019, 'A new bounded degree hierarchy with SOCP relaxations for global polynomial optimization and conic convex semi-algebraic programs', Journal of Global Optimization, 75, pp. 885 - 919, http://dx.doi.org/10.1007/s10898-019-00831-9

Chieu NH; Chuong TD; Jeyakumar V; Li G, 2019, 'A copositive Farkas lemma and minimally exact conic relaxations for robust quadratic optimization with binary and quadratic constraints', Operations Research Letters, 47, pp. 530 - 536, http://dx.doi.org/10.1016/j.orl.2019.09.013

Feng J; Liu L; Wu D; Li G; Beer M; Gao W, 2019, 'Dynamic reliability analysis using the extended support vector regression (X-SVR)', Mechanical Systems and Signal Processing, 126, pp. 368 - 391, http://dx.doi.org/10.1016/j.ymssp.2019.02.027

Feng J; Li Q; Sofi A; Li G; Wu D; Gao W, 2019, 'Uncertain Structural Free Vibration Analysis with Non-Probabilistic Spatially Varying Parameters', ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 5, http://dx.doi.org/10.1115/1.4041501

Tang C; Jian J; Li G, 2019, 'A proximal-projection partial bundle method for convex constrained minimax problems', Journal of Industrial and Management Optimization, 15, pp. 757 - 774, http://dx.doi.org/10.3934/jimo.2018069

Liu Z; Yang C; Gao W; Wu D; Li G, 2019, 'Nonlinear behaviour and stability of functionally graded porous arches with graphene platelets reinforcements', International Journal of Engineering Science, 137, pp. 37 - 56, http://dx.doi.org/10.1016/j.ijengsci.2018.12.003

Hu S; Li G, 2018, 'Convergence rate analysis for the higher order power method in best rank one approximations of tensors', Numerische Mathematik, 140, pp. 993 - 1031, http://dx.doi.org/10.1007/s00211-018-0981-3

Li G; Pong TK, 2018, 'Calculus of the Exponent of Kurdyka–Łojasiewicz Inequality and Its Applications to Linear Convergence of First-Order Methods', Foundations of Computational Mathematics, 18, pp. 1199 - 1232, http://dx.doi.org/10.1007/s10208-017-9366-8

Goberna MA; Jeyakumar V; Li G; Vicente-Pérez J, 2018, 'Guaranteeing highly robust weakly efficient solutions for uncertain multi-objective convex programs', European Journal of Operational Research, 270, pp. 40 - 50, http://dx.doi.org/10.1016/j.ejor.2018.03.018

Bomze IM; Jeyakumar V; Li G, 2018, 'Extended trust-region problems with one or two balls: exact copositive and Lagrangian relaxations', Journal of Global Optimization, 71, pp. 551 - 569, http://dx.doi.org/10.1007/s10898-018-0607-4

Chieu NH; Feng JW; Gao W; Li G; Wu D, 2018, 'SOS-Convex Semialgebraic Programs and its Applications to Robust Optimization: A Tractable Class of Nonsmooth Convex Optimization', Set-Valued and Variational Analysis, 26, pp. 305 - 326, http://dx.doi.org/10.1007/s11228-017-0456-1

Li G; Mordukhovich BS; Nghia TTA; Phạm TS, 2018, 'Error bounds for parametric polynomial systems with applications to higher-order stability analysis and convergence rates', Mathematical Programming, 168, pp. 313 - 346, http://dx.doi.org/10.1007/s10107-016-1014-6

Chieu NH; Jeyakumar V; Li G; Mohebi H, 2018, 'Constraint qualifications for convex optimization without convexity of constraints : New connections and applications to best approximation', European Journal of Operational Research, 265, pp. 19 - 25, http://dx.doi.org/10.1016/j.ejor.2017.07.038

Chen H; Chen Y; Li G; Qi L, 2018, 'A semidefinite program approach for computing the maximum eigenvalue of a class of structured tensors and its applications in hypergraphs and copositivity test', Numerical Linear Algebra with Applications, 25, http://dx.doi.org/10.1002/nla.2125

Jeyakumar V; Li G, 2018, 'Exact second-order cone programming relaxations for some nonconvex minimax quadratic optimization problems', SIAM Journal on Optimization, 28, pp. 760 - 787, http://dx.doi.org/10.1137/16M1058480

Feng J; Wu D; Gao W; Li G; Wu D, 2018, 'Hybrid uncertain natural frequency analysis for structures with random and interval fields', Computer Methods in Applied Mechanics and Engineering, 328, pp. 365 - 389, http://dx.doi.org/10.1016/j.cma.2017.09.004

Che M; Li G; Qi L; Wei Y, 2017, 'Pseudo-spectra theory of tensors and tensor polynomial eigenvalue problems', Linear Algebra and Its Applications, 533, pp. 536 - 572, http://dx.doi.org/10.1016/j.laa.2017.07.026

Li G; Liu T; Pong TK, 2017, 'Peaceman–Rachford splitting for a class of nonconvex optimization problems', Computational Optimization and Applications, 68, pp. 407 - 436, http://dx.doi.org/10.1007/s10589-017-9915-8

Feng J; Wu D; Gao W; Li G, 2017, 'Uncertainty analysis for structures with hybrid random and interval parameters using mathematical programming approach', Applied Mathematical Modelling, 48, pp. 208 - 232, http://dx.doi.org/10.1016/j.apm.2017.03.066

Chieu NH; Jeyakumar V; Li G, 2017, 'A convergent hierarchy of SDP relaxations for a class of hard robust global polynomial optimization problems', Operations Research Letters, 45, pp. 325 - 333, http://dx.doi.org/10.1016/j.orl.2017.04.005

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