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Dominique OrbanDépartement de mathématiques et de génie industriel
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Dans le contexte de cette page, le nuage de mots a été généré à partir des publications de l'auteur Dominique Orban. Les mots présents dans ce nuage proviennent des titres, résumés et mots-clés des articles et travaux de recherche de cet auteur. En analysant ce nuage de mots, vous pouvez obtenir un aperçu des sujets et des domaines de recherche les plus récurrents et significatifs dans les travaux de cet auteur.Le nuage de mots est un outil utile pour identifier les tendances et les thèmes principaux dans un corpus de textes, facilitant ainsi la compréhension et l'analyse des contenus de manière visuelle et intuitive.
Aravkin, A., Baraldi, R., Leconte, G., & Orban, D. (2024). Corrigendum: A proximal quasi-Newton trust-region method for nonsmooth regularized optimization. (Rapport technique n° G-2021-12-SM). Lien externe
Aravkin, A., Baraldi, R., & Orban, D. (2024). A proximal quasi-Newton trust-region method for nonsmooth regularized optimization. (Rapport technique n° G-2021-12). Lien externe
Aravkin, A. Y., Baraldi, R., & Orban, D. (2024). A Levenberg-Marquardt method for nonsmooth regularized least squarres. SIAM Journal on Scientific Computing, 46(4), A2557-A2581. Lien externe
Aravkin, A., Baraldi, R., & Orban, D. (2022). A Levenberg-Marquardt method for nonsmooth regularized least squares. (Rapport technique n° G-2022-58). Lien externe
Aravkin, A. Y., Baraldi, R., & Orban, D. (2022). A proximal quasi-Newton trust-region method for nonsmooth regularized optimization. SIAM Journal on Optimization, 32(2), 900-929. Lien externe
Angla, C., Bigeon, J., & Orban, D. (2020). Modeling and solving bundle adjustment problems. (Rapport technique n° G-2020-42). Lien externe
Arreckx, S., & Orban, D. (2018). A regularized factorization-free method for equality-constrained optimization. SIAM Journal on Optimization, 28(2), 1613-1639. Lien externe
Arreckx, S., Lambe, A., Martins, J. R. R. A., & Orban, D. (2016). A matrix-free augmented lagrangian algorithm with application to large-scale structural design optimization. Optimization and Engineering, 17(2), 359-384. Lien externe
Arreckx, S., Orban, D., & Van Omme, N. (2016). NLP.py: An object-oriented environment for large-scale optimization. (Rapport technique n° G-2016-42). Lien externe
Arreckx, S., & Orban, D. (2016). A Regularized Factorization-Free Method for Equality-Constrained Optimization. (Rapport technique n° G-2016-65). Lien externe
Arreckx, S., Lambe, A., Martins, J. R. R. A., & Orban, D. (2014). A matrix-free augmented Lagrangian algorithm with application to large-scale structural design optimization. (Rapport technique n° G-2014-71). Lien externe
Audet, C., Dang, C.-K., & Orban, D. (2014). Optimization of algorithms with OPAL. Mathematical Programming Computation, 6(3), 233-254. Lien externe
Audet, C., Dang, C. K., & Orban, D. (2013). Efficient use of parallelism in algorithmic parameter optimization applications. Optimization Letters, 7(3), 421-433. Lien externe
Armand, P., Benoist, J., & Orban, D. (2013). From Global to Local Convergence of Interior Methods for Nonlinear Optimization. Optimization Methods & Software, 28(5), 1051-1080. Lien externe
Arioli, M., & Orban, D. (2013). Iterative Methods for Symmetric Quasi-Definite Linear Systems--Part I: Theory. (Rapport technique n° G-2013-32). Lien externe
Armand, P., & Orban, D. (2012). The squared slacks transformation in nonlinear programming. SQU Journal for Science, 17(1), 22-29. Disponible
Ayotte-Sauvé, É., Chugunova, M., Cortes, B., Lina, A., Majumdar, A., Orban, D., Prior, C., & Zalzal, V. (août 2011). On Equidistant Points on a Curve [Communication écrite]. 4e Atelier de résolution de problèmes industriels de Montréal, Montréal, QC, Canada. Lien externe
Audet, C., Dang, C.-K., & Orban, D. (2010). Algorithmic parameter optimization of the DFO method with the OPAL framework. Dans Naono, K., Teranishi, K., Cavazos, J., & Suda, R. (édit.), Software Automatic Tuning: From Concepts to State-of-the-Art Results (p. 255-274). Lien externe
Armand, P., Kiselev, A., Marcotte, O., & Orban, D. (2009). Self calibration of a pinhole camera. Mathematics-in-Industry Case Studies, 1, 81-98. Lien externe
Armand, P., Benoist, J., & Orban, D. (2008). Dynamic Updates of the Barrier Parameter in Primal-Dual Methods for Nonlinear Programming. Computational Optimization and Applications, 41(1), 1-25. Lien externe
Audet, C., & Orban, D. (2006). Finding Optimal Algorithmic Parameters Using Derivative-Free Optimization. SIAM Journal on Optimization, 17(3), 642-664. Lien externe
Bigeon, J., Orban, D., & Raynaud, P. (2023). A framework around limited-memory partitioned quasi-Newton methods. (Rapport technique n° G-2023-17). Lien externe
Bourhis, J., Dussault, J.-P., & Orban, D. (2019). Étude du comportement des méthodes BFGS et L-BFGS pour résoudre un sous-problème de région de confiance. (Rapport technique n° G-2019-64). Lien externe
Buttari, A., Orban, D., Ruiz, D., & Titley-Peloquin, D. (2019). A tridiagonalization method for symmetric saddle-point systems. SIAM Journal on Scientific Computing, 41(5), S409-S432. Lien externe
Buttari, A., Orban, D., Ruiz, D., & Titley-Peloquin, D. (2018). A tridiagonalization method for symmetric saddle-point and quasi-definitive system. (Rapport technique n° G-2018-42). Lien externe
Beauthier, C., Crélot, A. S., Orban, D., Sainvitu, C., & Sartenaer, A. (janvier 2016). Surrogate Management in Mixed-Variable Derivative-Free Optimization [Communication écrite]. 30th Annual Conference of the Belgian Operational Research Society (ORBEL 30), Louvain-la-Neuve, Belgique. Non disponible
Crélot, A.-S., Beauthier, C., Orban, D., Sainvitu, C., & Sartenaer, A. (2017). Combining surrogate strategies with MADS for mixed-variable derivative-free optimization. (Rapport technique n° G-2017-70). Lien externe
Côté, P., Demeester, K., Orban, D., & Towhidi, M. (2017). Numerical methods for stochastic dynamic programming with application to hydropower optimization. (Rapport technique n° G-2017-64). Lien externe
Coulibaly, Z., & Orban, D. (2012). An ℓ₁ Elastic Interior-Point Method for Mathematical Programs With Complementarity Constraints. SIAM Journal on Optimization, 22(1), 187-211. Lien externe
Conn, A. R., Gould, N. I. M., Orban, D., & Toint, P. L. (2000). A primal-dual trust-region algorithm for non-convex nonlinear programming. Mathematical Programming, 87(2), 215-249. Lien externe
Diouane, Y., Gürol, S., Mouhtal, O., & Orban, D. (2024). An efficient scaled spectral preconditioner for sequences of symmetric positive definite linear systems. (Rapport technique n° G-2024-66). Lien externe
Diouane, Y., Laghdaf Habiboullah, M., & Orban, D. (2024). A proximal modified quasi-Newton method for nonsmooth regularized optimization. (Rapport technique n° G-2024-64). Lien externe
Diouane, Y., Laghdaf Habiboullah, M., & Orban, D. (2024). Complexity of trust-region methods in the presence of unbounded Hessian approximations. (Rapport technique n° G-2024-43). Lien externe
Diouane, Y., Golier, M., & Orban, D. (2024). A nonsmooth exact penalty method for equality-constrained optimization : complexity and implementation. (Rapport technique n° G-2024-55). Lien externe
Dussault, J.-P., Migot, T., & Orban, D. (2023). Scalable adaptive cubic regularization methods. Mathematical Programming, 35 pages. Lien externe
di Serafino, D., & Orban, D. (2021). Constraint-Preconditioned Krylov Solvers for Regularized Saddle-Point Systems. SIAM Journal on Scientific Computing, 43(2), 1001-1026. Lien externe
Dehghani, M., Lambe, A., & Orban, D. (2020). A regularized interior-point method for constrained linear least squares. INFOR: Information Systems and Operational Research, 58(2), 202-224. Lien externe
Dahito, M.-A., & Orban, D. (2019). The conjugate residual method in linesearch and trust-region methods. SIAM Journal on Optimization, 29(3), 1988-2025. Lien externe
di Serafino, D., & Orban, D. (2019). Constraint-preconditioned Krylov solvers for regularized saddle-point systems. (Rapport technique). Lien externe
Dehghani, M., Lambe, A., & Orban, D. (2018). A regularized interior-point method for constrained linear least squares. (Rapport technique n° G-2018-07). Lien externe
Dahito, M.-A., & Orban, D. (2018). The conjugate residual method in linesearch and trust-region methods. (Rapport technique n° G-2018-50). Lien externe
Dehghani, A., Goffin, J. L., & Orban, D. (2017). A primal-dual regularized interior-point method for semidefinite programming. Optimization Methods & Software, 32(1), 193-219. Lien externe
Dussault, J.-P., & Orban, D. (2015). A Scalable Implementation of Adaptive Cubic Regularization Methods Using Shifted Linear Systems. (Rapport technique n° G-2015-109). Lien externe
Dehghani, A., Goffin, J.-L., & Orban, D. (2012). Solving Unconstrained Nonlinear Programs Using ACCPM. (Rapport technique n° G-2012-02). Lien externe
Estrin, R., Friedlander, M. P., Orban, D., & Saunders, M. A. (2020). Implementing a smooth exact penalty function for equality-constrained nonlinear optimization. SIAM Journal on Scientific Computing, 42(3), A1809-A1835. Lien externe
Estrin, R., Friedlander, M. P., Orban, D., & Saunders, M. A. (2020). Implementing a smooth exact penalty function for general constrained nonlinear optimization. SIAM Journal on Scientific Computing, 42(3), A1836-A1859. Lien externe
Estrin, R., Friedlander, M. P., Orban, D., & Saunders, M. A. (2019). Implementing a smooth exact penalty function for constrained nonlinear optimization. (Rapport technique n° G-2019-27). Lien externe
Estrin, R., Orban, D., & Saunders, M. A. (2019). Euclidean-norm error bounds for SYMMLQ and CG. SIAM Journal on Matrix Analysis and Applications, 40(1), 235-253. Lien externe
Estrin, R., Friedlander, M. P., Orban, D., & Saunders, M. A. (2019). Implementing a smooth exact penalty function for equality-constrained nonlinear optimization. (Rapport technique n° G-2019-04). Lien externe
Estrin, R., Orban, D., & Saunders, M. A. (2019). LNLQ: An iterative method for least-norm problems with an error minimization property. SIAM Journal on Matrix Analysis and Applications, 40(3), 1102-1124. Lien externe
Estrin, R., Orban, D., & Saunders, M. A. (2019). LSLQ: An iterative method for linear least-squares with an error minimization property. SIAM Journal on Matrix Analysis and Applications, 40(1), 254-275. Lien externe
Estrin, R., Orban, D., & Saunders, M. A. (2018). LNLQ: An iterative method for least-norm problems with an error minimization property. (Rapport technique n° G-2018-40). Lien externe
Estrin, R., Orban, D., & Saunders, M. A. (2017). LSLQ: An Iterative Method for Linear Least-Squares with an Error Minimization Property. (Rapport technique n° G-2017-05). Lien externe
Estrin, R., Orban, D., & Saunders, M. A. (2016). Estimates of the 2-Norm Forward Error for SYMMLQ and CG. (Rapport technique n° G-2016-70). Lien externe
Fowkes, J., Lister, A., Montoison, A., & Orban, D. (2024). LibHSL : the ultimate collection for large-scale scientific computation. (Rapport technique n° G-2024-06). Lien externe
Fowkes, J., Gould, N. I. M., Montoison, A., & Orban, D. (2023). GALAHAD 4 an open source library of Fortran packages with C and Matlab interfaces for continuous optimization' [Ensemble de données]. Lien externe
Friedlander, M. P., & Orban, D. (2012). A Primal-Dual Regularized Interior-Point Method for Convex Quadratic Programs. Mathematical Programming Computation, 4(1), 71-107. Lien externe
Fourer, R., Maheshwari, C., Neumaier, A., Orban, D., & Schichl, H. (2010). Convexity and Concavity Detection in Computational Graphs: Tree Walks for Convexity Assessment. INFORMS Journal on Computing, 22(1), 26-43. Lien externe
Fourer, R., & Orban, D. (2010). The DrAMPL Meta Solver for Optimization Problem Analysis. Computational Management Science, 7(4), 437-463. Lien externe
Ghannad, A., Orban, D., & Saunders, M. A. (2021). Linear systems arising in interior methods for convex optimization: a symmetric formulation with bounded condition number. Optimization Methods and Software, 37(4), 1344-1369. Lien externe
Ghannad, A., Orban, D., & Saunders, M. A. (2020). A symmetric formulation of the linear system arising in interior methods for convex optimization with bounded condition number. (Rapport technique n° G-2020-37). Lien externe
Goussard, Y., McLaughlin, M., & Orban, D. (2017). Factorization-free methods for computed tomography. (Rapport technique n° G-2017-65). Lien externe
Gould, N. I. M., Orban, D., & Toint, P. L. (2015). CUTEst: a Constrained and Unconstrained Testing Environment with safe threads for mathematical optimization. Computational Optimization and Applications, 60(3), 545-557. Lien externe
Gould, N. I. M., Orban, D., & Toint, P. L. (janvier 2014). An interior-point 1-penalty method for nonlinear optimization [Communication écrite]. 3rd International Conference on Numerical Analysis and Optimization: Theory, Methods, Applications and Technology Transfer (NAOIII-2014), Muscat, Oman. Lien externe
Greif, C., Moulding, E., & Orban, D. (2014). Bounds on Eigenvalues of matrices arising from interior-point methods. SIAM Journal on Optimization, 24(1), 49-83. Lien externe
Gould, N., Orban, D., & Rees, T. (2014). Projected Krylov methods for saddle-point systems. SIAM Journal on Matrix Analysis and Applications, 35(4), 1329-1343. Lien externe
Gould, N. I. M., Orban, D., & Robinson, D. P. (2013). Trajectory-following methods for large-scale degenerate convex quadratic programming. Mathematical Programming Computation, 5(2), 113-142. Lien externe
Gould, N. I. M., Orban, D., & Toint, P. L. (2008). LANCELOT_SIMPLE: A Simple Interface for LANCELOT-B. (Rapport technique n° G-2008-11). Lien externe
Gould, N., Orban, D., & Toint, P. (2005). Numerical methods for large-scale nonlinear optimization. Acta Numerica, 14, 299-361. Lien externe
Gould, N. I. M., Orban, D., Sartenaer, A., & Toint, P. L. (2005). Sensitivity of trust-region algorithms to their parameters. 4OR, 3(3), 227-241. Lien externe
Gould, N. I. M., Orban, D., & Toint, P. L. (2003). CUTEr and SifDec: A Constrained and Unconstrained Testing Environment, Revisited. ACM Transactions on Mathematical Software, 29(4), 373-394. Lien externe
Gould, N. I. M., Orban, D., & Toint, P. L. (2003). GALAHAD, a Library of Thread-safe Fortran 90 Packages for Large-scale Nonlinear Optimization. ACM Transactions on Mathematical Software, 29(4), 353-372. Lien externe
Gould, N. I. M., Orban, D., Sartenaer, A., & Toint, P. L. (2002). Componentwise fast convergence in the solution of full-rank systems of nonlinear equations. Mathematical Programming, 92(3), 481-508. Lien externe
Gould, N. I. M., Orban, D., & Toint, P. L. (2002). Results from a Numerical Evaluation of LANCELOT B. (Rapport technique n° NAGIR-2002-1). Lien externe
Gould, N. I. M., Orban, D., Sartenaer, A., & Toint, P. L. (2001). Superlinear Convergence of Primal-Dual Interior Point Algorithms for Nonlinear Programming. SIAM Journal on Optimization, 11(4), 974-1002. Lien externe
Huang, N., Dai, Y.-H., Orban, D., & Saunders, M. A. (2024). An inexact augmented Lagrangian algorithm for unsymmetric saddle-point systems. (Rapport technique n° G-2024-30). Lien externe
Huang, N., Dai, Y.-H., Orban, D., & Saunders, M. A. (2023). On GSOR, the Generalized Successive Overrelaxation Method for Double Saddle-Point Problems. SIAM Journal on Scientific Computing, 45(5), A2185-A2206. Lien externe
Huang, N., Dai, Y.-H., Orban, D., & Saunders, M. A. (2023). Properties of semi-conjugate gradient methods for solving unsymmetric positive definite linear systems. Optimization Methods & Software, 38(5), 887-913. Lien externe
Huang, N., Dai, Y.-D., Orban, D., & Saunders, M. A. (2022). On GSOR, the generalized successive overrelaxation method for double saddle-point problems. (Rapport technique n° G-2022-35). Lien externe
Huang, N., Dai, Y.-D., Orban, D., & Saunders, M. A. (2022). A semi-conjugate gradient method for solving unsymmetric positive definite linear systems. (Rapport technique n° G-2022-25). Lien externe
Harvey, J.-P., Eriksson, G., Orban, D., & Chartrand, P. (2013). Global Minimization of the Gibbs Energy of Multicomponent Systems Involving the Presence of Order/Disorder Phase Transitions. American Journal of Science, 313(3), 199-241. Lien externe
Harvey, J.-P., Chartrand, P., Eriksson, G., & Orban, D. (septembre 2010). Gibbs energy minimization challenges using implicit variables solution models [Communication écrite]. Discussion meeting on thermodynamics of alloys (TOFA 2010), Porto, Portugal. Lien externe
Leconte, G., & Orban, D. (2024). RipQP: A multi-precision regularized predictor-corrector method for convex quadratic optimization. (Rapport technique n° G-2021-03). Lien externe
Leconte, G., & Orban, D. (2024). An interior-point trust-region method for nonsmooth regularized bound-constrained optimization. (Rapport technique n° G-2024-17). Lien externe
Leconte, G., & Orban, D. (2024). The indefinite proximal gradient method. Computational Optimization and Applications, 43 pages. Lien externe
Leconte, G., & Orban, D. (2023). The indefinite proximal gradient method. (Rapport technique n° G-2023-37). Lien externe
Leconte, G., & Orban, D. (2023). Complexity of trust-region with unbounded Hessian approximations for smooth and nonsmooth optimization. (Rapport technique n° G-2023-65). Lien externe
Lakhmiri, D., Orban, D., & Lodi, A. (2022). A stochastic proximal method for nonsmooth regularized finite sum optimization. (Rapport technique n° G-2022-27). Lien externe
Lotfi, S., Orban, D., & Lodi, A. (2021). Stochastic adaptive regularization with dynamic sampling for machine learning. (Rapport technique n° G-2020-51). Lien externe
Lotfi, S., Bonniot de Ruisselet, T., Orban, D., & Lodi, A. (2020). Stochastic damped L-BFGS with controlled norm of the Hessian approximation. (Rapport technique n° 2020-52). Lien externe
Monnet, D., & Orban, D. (2025). A multi-precision quadratic regularization method for unconstrained optimization with rounding error analysis. Computational Optimization and Applications, 35 pages. Lien externe
Montoison, A., Orban, D., & Saunders, M. A. (2025). MinAres: An Iterative Solver for Symmetric Linear Systems. SIAM Journal on Matrix Analysis and Applications, 46(1), 509-529. Lien externe
Migot, T., Orban, D., & Siqueira, A. S. (2024). JSOSuite.jl: Solving continuous optimization problems with JuliaSmoothOptimizers. JuliaCon Proceedings, 6(63), 161-161. Disponible
Migot, T., Orban, D., & Soares Siquiera, A. (2024). JSOSuite.jl: Solving continuous optimization problems with JuliaSmoothOptimizers. (Rapport technique n° G-2024-52). Lien externe
Montoison, A., & Orban, D. (2023). Krylov.jl: A Julia basket of hand-picked Krylov methods. The Journal of Open Source Software, 8(89), 5187-5187. Disponible
Monnet, D., & Orban, D. (2023). A multi-precision quadratic regularization method for unconstrained optimization with rouding error analysis. (Rapport technique n° G-2023-18). Lien externe
Montoison, A., & Orban, D. (2023). Krylov.jl: A Julia basket of hand-picked Krylov methods. (Rapport technique n° G-2022-50). Lien externe
Montoison, A., & Orban, D. (2023). GPMR : an iterative method for unsymmetric partitioned lliear systems. SIAM Journal on Matrix Analysis and Applications, 44(1), 293-311. Lien externe
Montoison, A., Orban, D., & Saunders, M. A. (2023). MinAres : an iterative solver for symmetric linear systems. (Rapport technique n° G-2023-40). Lien externe
Migot, T., Orban, D., & Soares Siquiera, A. (2022). PDENLPModels.jl: An NLPModel API for optimization problems with PDE-constraints. (Rapport technique n° G-2022-42). Lien externe
Migot, T., Orban, D., & Siqueira, A. S. (2022). DCISolver.jl: A Julia Solver for Nonlinear Optimization using Dynamic Control of Infeasibility. Journal of Open Source Software, 7(70), 4 pages. Lien externe
Migot, T., Orban, D., & Soares Siqueira, A. (2022). PDENLP models.jl : an NLP model API for optimization problems with PDE-constraints. Journal of Open Source Software, 5 pages. Disponible
Migot, T., Orban, D., & Soares Siquiera, A. (2021). DCISolver.jl: A Julia solver for nonlinear optimization using dynamic control of infeasibility. (Rapport technique n° G-2021-67). Lien externe
Montoison, A., & Orban, D. (2021). GPMR: An iterative method for unsymmetric partitioned linear systems. (Rapport technique n° G-2021-62). Lien externe
Montoison, A., & Orban, D. (2021). TriCG and TriMR: Two iterative methods for symmetric and quasi-definite systems. (Rapport technique n° G-2020-41). Lien externe
Ma, D., Orban, D., & Saunders, M. A. (2021). A Julia implementation of Algorithm NCL for constrained optimization. (Rapport technique n° 2021-02). Lien externe
Ma, D., Orban, D., & Saunders, M. A. (janvier 2020). A Julia Implementation of Algorithm NCL for Constrained Optimization [Communication écrite]. 5th International Conference on Numerical Analysis and Optimization: Theory, Methods, Applications and Technology Transfer (NAOV 2020), Muscat, Oman. Lien externe
Montoison, A., & Orban, D. (2021). TRICG and TRIMR: Two iterative methods for symmetric quasi-definite systems. SIAM Journal on Scientific Computing, 43(4), A2502-A2525. Lien externe
Montoison, A., & Orban, D. (2020). BILQ: An iterative method for nonsymmetric linear systems with a quasi-minimum error property. SIAM Journal on Matrix Analysis and Applications, 41(3), 1145-1166. Lien externe
Mestdagh, G., Goussard, Y., & Orban, D. (2020). Scaled projected-directions methods with application to transmission tomography. Optimization and Engineering, 21(4), 1537-1561. Lien externe
Mestdagh, G., Goussard, Y., & Orban, D. (2019). Scaled projected-directions methods with application to transmission tomography. (Rapport technique n° G-2019-60). Lien externe
Montoison, A., & Orban, D. (2019). BiLQ: An iterative method for nonsymmetric linear systems with a quasi-minimum property. (Rapport technique n° G-2019-71). Lien externe
Ma, D., Judd, K. L., Orban, D., & Saunders, M. A. (janvier 2017). Stabilized optimization via an NCL algorithm [Communication écrite]. 4th International Conference on Numerical Analysis and Optimization (NAO-IV 2017), Muscat, Oman. Lien externe
Ma, D., Judd, K., Orban, D., & Saunders, M. A. (2017). Stabilized optimization via an NCL algorithm. (Rapport technique n° G-2017-108). Lien externe
Menvielle, N., Goussard, Y., Orban, D., & Soulez, G. (août 2005). Reduction of beam-hardening artifacts in X-ray CT [Communication écrite]. 2005 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Lien externe
Orban, D. (2022). Computing a sparse projection into a box. (Rapport technique n° G-2022-12). Lien externe
Orban, D., & Siqueira, A. S. (2020). A regularization method for constrained nonlinear least squares. Computational Optimization and Applications, 76(3), 961-989. Lien externe
Orban, D., & Siqueira, A. S. (2019). A regularization method for constrained nonlinear least squares. (Rapport technique n° G-2019-17). Lien externe
Orban, D. (2018). Introduction to computation and programming using Python, Second edition, with application to understanding data (review). SIAM Review, 60(2), 483-485. Lien externe
Orban, D., & Arioli, M. (2017). Iterative solution of symmetric quasi-definite linear systems. Lien externe
Orban, D. (2015). A Collection of Linear Systems Arising from Interior-Point Methods for Quadratic Optimization. (Rapport technique n° G-2015-117). Lien externe
Orban, D. (2015). Limited-memory LDL⊤ factorization of symmetric quasi-definite matrices with application to constrained optimization. Numerical Algorithms, 70(1), 9-41. Lien externe
Orban, D. (2015). Sqd-Collection: Initial Release [Ensemble de données]. Lien externe
Orban, D. (2014). The Projected Golub-Kahan Process for Constrained Linear Least-Squares Problems. (Rapport technique n° G-2014-15). Lien externe
Orban, D. (2011). Templating and Automatic Code Generation for Performance with Python. (Rapport technique n° G-2011-30). Lien externe
Orban, D. (2009). The Lightning AMPL Tutorial. A Guide for Nonlinear Optimization Users. (Rapport technique n° G-2009-66). Lien externe
Orban, D. (2008). Projected Krylov Methods for Unsymmetric Augmented Systems. (Rapport technique n° G-2008-46). Lien externe
Raynaud, P., Orban, D., & Bigeon, J. (2023). Partially-separable loss to parallellize partitioned neural network training. (Rapport technique n° G-2023-36). Lien externe
Raynaud, P., Orban, D., & Bigeon, J. (2023). PLSR1 : a limited-memory partioned quasi-Newton optimizer for partially-separable loss functions. (Rapport technique n° G-2023-41). Lien externe
Raynaud, P., & Orban, D. (septembre 2023). Limited-memory stochastic partitioned quasi-newton training [Affiche]. Edge Intelligence Workshop, Montreal, Qc, Canada (1 page). Lien externe
Raymond, V., Soumis, F., & Orban, D. (2010). A new version of the improved primal simplex for degenerate linear programs. Computers & Operations Research, 37(1), 91-98. Lien externe
Siqueira, A. S., & Orban, D. (juin 2018). Developing new optimization methods with packages from the JuliaSmoothOptimizers organisation [Communication écrite]. 2nd annual JuMP-Dev Workshop, Bordeaux, France (30 pages). Non disponible
Sinqueira, A. S., & Orban, D. (juillet 2018). A regularized interior-point method for constrained nonlinear least squares [Communication écrite]. 12th Brazilian Workshop on Continuous Optimization, Foz do Iguaçu, Brazil. Non disponible
Towhidi, M., & Orban, D. (2016). Customizing the solution process of COIN-ORs linear solvers with Python. Mathematical Programming Computation, 8(4), 377-391. Lien externe
Waltz, R. A., Morales, J. L., Nocedal, J., & Orban, D. (2006). An interior algorithm for nonlinear optimization that combines line search and trust region steps. Mathematical Programming, 107(3), 391-408. Lien externe
Wright, S. J., & Orban, D. (2002). Properties of the Log-Barrier Function on Degenerate Nonlinear Programs. Mathematics of Operations Research, 27(3), 585-613. Lien externe
