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Dussault, J.-P., Migot, T., & Orban, D. (2023). Scalable adaptive cubic regularization methods. Mathematical Programming, 35 pages. 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
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). 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
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
