Philippe L. Toint
Orcid: 0000-0002-6166-1860Affiliations:
- University of Namur, Belgium
According to our database1,
Philippe L. Toint
authored at least 128 papers
between 1981 and 2023.
Collaborative distances:
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on orcid.org
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on id.loc.gov
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Bibliography
2023
Multilevel Objective-Function-Free Optimization with an Application to Neural Networks Training.
SIAM J. Optim., December, 2023
Optim. Methods Softw., November, 2023
Convergence Properties of an Objective-Function-Free Optimization Regularization Algorithm, Including an \(\boldsymbol{\mathcal{O}(\epsilon^{-3/2})}\) Complexity Bound.
SIAM J. Optim., September, 2023
Comput. Optim. Appl., March, 2023
J. Optim. Theory Appl., February, 2023
CoRR, 2023
A Block-Coordinate Approach of Multi-level Optimization with an Application to Physics-Informed Neural Networks.
CoRR, 2023
2022
SIAM J. Matrix Anal. Appl., September, 2022
ACM Trans. Math. Softw., 2022
Adaptive regularization for nonconvex optimization using inexact function values and randomly perturbed derivatives.
J. Complex., 2022
Trust-region algorithms: Probabilistic complexity and intrinsic noise with applications to subsampling techniques.
EURO J. Comput. Optim., 2022
CoRR, 2022
2021
Numer. Linear Algebra Appl., 2021
An algorithm for the minimization of nonsmooth nonconvex functions using inexact evaluations and its worst-case complexity.
Math. Program., 2021
High-order evaluation complexity for convexly-constrained optimization with non-Lipschitzian group sparsity terms.
Math. Program., 2021
Hölder Gradient Descent and Adaptive Regularization Methods in Banach Spaces for First-Order Points.
CoRR, 2021
Quadratic and Cubic Regularisation Methods with Inexact function and Random Derivatives for Finite-Sum Minimisation.
Proceedings of the 2021 21st International Conference on Computational Science and Its Applications (ICCSA), Cagliari, Italy, September 13-16, 2021, 2021
2020
Sharp Worst-Case Evaluation Complexity Bounds for Arbitrary-Order Nonconvex Optimization with Inexpensive Constraints.
SIAM J. Optim., 2020
A concise second-order complexity analysis for unconstrained optimization using high-order regularized models.
Optim. Methods Softw., 2020
Comput. Optim. Appl., 2020
2019
ACM Trans. Math. Softw., 2019
Complexity of Partially Separable Convexly Constrained Optimization with Non-Lipschitzian Singularities.
SIAM J. Optim., 2019
Universal Regularization Methods: Varying the Power, the Smoothness and the Accuracy.
SIAM J. Optim., 2019
Adaptive Regularization Algorithms with Inexact Evaluations for Nonconvex Optimization.
SIAM J. Optim., 2019
Optimality of orders one to three and beyond: Characterization and evaluation complexity in constrained nonconvex optimization.
J. Complex., 2019
2018
Math. Comput., 2018
Second-Order Optimality and Beyond: Characterization and Evaluation Complexity in Convexly Constrained Nonlinear Optimization.
Found. Comput. Math., 2018
Deterministic and stochastic inexact regularization algorithms for nonconvex optimization with optimal complexity.
CoRR, 2018
2017
BFO, A Trainable Derivative-free Brute Force Optimizer for Nonlinear Bound-constrained Optimization and Equilibrium Computations with Continuous and Discrete Variables.
ACM Trans. Math. Softw., 2017
Worst-case evaluation complexity of regularization methods for smooth unconstrained optimization using Hölder continuous gradients.
Optim. Methods Softw., 2017
Math. Program., 2017
Corrigendum: On the complexity of finding first-order critical points in constrained nonlinear optimization.
Math. Program., 2017
Worst-case evaluation complexity for unconstrained nonlinear optimization using high-order regularized models.
Math. Program., 2017
Improved second-order evaluation complexity for unconstrained nonlinear optimization using high-order regularized models.
CoRR, 2017
Evaluation complexity bounds for smooth constrained nonlinear optimisation using scaled KKT conditions, high-order models and the criticality measure $χ$.
CoRR, 2017
Partially separable convexly-constrained optimization with non-Lipschitzian singularities and its complexity.
CoRR, 2017
2016
Evaluation Complexity for Nonlinear Constrained Optimization Using Unscaled KKT Conditions and High-Order Models.
SIAM J. Optim., 2016
Numerical experience with a derivative-free trust-funnel method for nonlinear optimization problems with general nonlinear constraints.
Optim. Methods Softw., 2016
Simple examples for the failure of Newton's method with line search for strictly convex minimization.
Math. Program., 2016
2015
On the Evaluation Complexity of Constrained Nonlinear Least-Squares and General Constrained Nonlinear Optimization Using Second-Order Methods.
SIAM J. Numer. Anal., 2015
A Stochastic and Flexible Activity Based Model for Large Population. Application to Belgium.
J. Artif. Soc. Soc. Simul., 2015
A derivative-free trust-funnel method for equality-constrained nonlinear optimization.
Comput. Optim. Appl., 2015
CUTEst: a Constrained and Unconstrained Testing Environment with safe threads for mathematical optimization.
Comput. Optim. Appl., 2015
2014
On the complexity of finding first-order critical points in constrained nonlinear optimization.
Math. Program., 2014
2013
On the Evaluation Complexity of Cubic Regularization Methods for Potentially Rank-Deficient Nonlinear Least-Squares Problems and Its Relevance to Constrained Nonlinear Optimization.
SIAM J. Optim., 2013
Nonlinear stepsize control, trust regions and regularizations for unconstrained optimization.
Optim. Methods Softw., 2013
A note about the complexity of minimizing Nesterov's smooth Chebyshev-Rosenbrock function.
Optim. Methods Softw., 2013
Preconditioning and globalizing conjugate gradients in dual space for quadratically penalized nonlinear-least squares problems.
Comput. Optim. Appl., 2013
2012
On the Oracle Complexity of First-Order and Derivative-Free Algorithms for Smooth Nonconvex Minimization.
SIAM J. Optim., 2012
Evaluation complexity of adaptive cubic regularization methods for convex unconstrained optimization.
Optim. Methods Softw., 2012
Math. Program., 2012
J. Complex., 2012
Using approximate secant equations in limited memory methods for multilevel unconstrained optimization.
Comput. Optim. Appl., 2012
Updating the regularization parameter in the adaptive cubic regularization algorithm.
Comput. Optim. Appl., 2012
2011
Range-Space Variants and Inexact Matrix-Vector Products in Krylov Solvers for Linear Systems Arising from Inverse Problems.
SIAM J. Matrix Anal. Appl., 2011
On the Evaluation Complexity of Composite Function Minimization with Applications to Nonconvex Nonlinear Programming.
SIAM J. Optim., 2011
An active-set trust-region method for derivative-free nonlinear bound-constrained optimization.
Optim. Methods Softw., 2011
Numerische Mathematik, 2011
Numer. Linear Algebra Appl., 2011
Adaptive cubic regularisation methods for unconstrained optimization. Part II: worst-case function- and derivative-evaluation complexity.
Math. Program., 2011
Adaptive cubic regularisation methods for unconstrained optimization. Part I: motivation, convergence and numerical results.
Math. Program., 2011
Approximating Hessians in unconstrained optimization arising from discretized problems.
Comput. Optim. Appl., 2011
2010
Estimating Nonparametric Random Utility Models with an Application to the Value of Time in Heterogeneous Populations.
Transp. Sci., 2010
Convergence of a Regularized Euclidean Residual Algorithm for Nonlinear Least-Squares.
SIAM J. Numer. Anal., 2010
Self-Correcting Geometry in Model-Based Algorithms for Derivative-Free Unconstrained Optimization.
SIAM J. Optim., 2010
On the Complexity of Steepest Descent, Newton's and Regularized Newton's Methods for Nonconvex Unconstrained Optimization Problems.
SIAM J. Optim., 2010
Optim. Methods Softw., 2010
Numerical experience with a recursive trust-region method for multilevel nonlinear bound-constrained optimization.
Optim. Methods Softw., 2010
Math. Program., 2010
2009
Optim. Methods Softw., 2009
2008
SIAM J. Optim., 2008
2007
FILTRANE, a Fortran 95 filter-trust-region package for solving nonlinear least-squares and nonlinear feasibility problems.
ACM Trans. Math. Softw., 2007
Optim. Methods Softw., 2007
2006
Exploiting problem structure in pattern search methods for unconstrained optimization.
Optim. Methods Softw., 2006
Convergence theory for nonconvex stochastic programming with an application to mixed logit.
Math. Program., 2006
Comput. Manag. Sci., 2006
2005
Optim. Methods Softw., 2005
2004
A Multidimensional Filter Algorithm for Nonlinear Equations and Nonlinear Least-Squares.
SIAM J. Optim., 2004
2003
ACM Trans. Math. Softw., 2003
GALAHAD, a library of thread-safe Fortran 90 packages for large-scale nonlinear optimization.
ACM Trans. Math. Softw., 2003
2002
Global Convergence of a Trust-Region SQP-Filter Algorithm for General Nonlinear Programming.
SIAM J. Optim., 2002
Componentwise fast convergence in the solution of full-rank systems of nonlinear equations.
Math. Program., 2002
2001
Superlinear Convergence of Primal-Dual Interior Point Algorithms for Nonlinear Programming.
SIAM J. Optim., 2001
Appl. Math. Lett., 2001
Global Convergence of a Hybrid Trust-Region SQP-Filter Algorithm for General Nonlinear Programming.
Proceedings of the System Modelling and Optimization XX, 2001
2000
Math. Program., 2000
MOS-SIAM Series on Optimization, SIAM, ISBN: 978-0-89871-985-7, 2000
1999
Math. Program., 1999
SQP Methods for Large-Scale Nonlinear Programming.
Proceedings of the System Modelling and Optimization: Methods, 1999
1997
On The Overspecification of Multinomial and Nested Logit Models Due to Alternative Specific Constants.
Transp. Sci., 1997
Non-monotone trust-region algorithms for nonlinear optimization subject to convex constraints.
Math. Program., 1997
Math. Program., 1997
A globally convergent Lagrangian barrier algorithm for optimization with general inequality constraints and simple bounds.
Math. Comput., 1997
On the Number of Inner Iterations Per Outer Iteration of a Globally Convergent Algorithm for Optimization with General Nonlinear Inequality Constraints and Simple Bounds.
Comput. Optim. Appl., 1997
1996
SIAM J. Sci. Comput., 1996
Convergence Properties of Minimization Algorithms for Convex Constraints Using a Structured Trust Region.
SIAM J. Optim., 1996
Convergence Properties of an Augmented Lagrangian Algorithm for Optimization with a Combination of General Equality and Linear Constraints.
SIAM J. Optim., 1996
Numerical experiments with the LANCELOT package (Release A) for large-scale nonlinear optimization.
Math. Program., 1996
1995
ACM Trans. Math. Softw., 1995
1994
On the use of an inverse shortest paths algorithm for recovering linearly correlated costs.
Math. Program., 1994
1993
Global Convergence of a Class of Trust Region Algorithms for Optimization Using Inexact Projections on Convex Constraints.
SIAM J. Optim., 1993
1992
LSNNO, a FORTRAN subroutine for solving large-scale nonlinear network optimization problems.
ACM Trans. Math. Softw., 1992
1991
Math. Program., 1991
1990
1986
Global convergence of the partitioned BFGS algorithm for convex partially separable optimization.
Math. Program., 1986
1984
Math. Program., 1984
1983
Forcing sparsity by projecting with respect to a non-diagonally weighted frobenius norm.
Math. Program., 1983
1981