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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. 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
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., & 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
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
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
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
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
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
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. (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
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). The indefinite proximal gradient method. Computational Optimization and Applications, 43 pages. Lien externe
Leconte, G., & Orban, D. (2023). Complexity of trust-region with unbounded Hessian approximations for smooth and nonsmooth optimization. (Non spécifié). 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
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
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
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
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
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
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., & 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