Coralia Cartis
Orcid: 0000-0002-0963-5550
According to our database1,
Coralia Cartis
authored at least 47 papers
between 2009 and 2024.
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Bibliography
2024
2023
Math. Program., May, 2023
Bound-constrained global optimization of functions with low effective dimensionality using multiple random embeddings.
Math. Program., March, 2023
EURO J. Comput. Optim., January, 2023
Cubic-quartic regularization models for solving polynomial subproblems in third-order tensor methods.
CoRR, 2023
Second-order methods for quartically-regularised cubic polynomials, with applications to high-order tensor methods.
CoRR, 2023
2022
2021
CoRR, 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
CoRR, 2020
2019
INFORMS J. Optim., April, 2019
Improving the Flexibility and Robustness of Model-based Derivative-free Optimization Solvers.
ACM Trans. Math. Softw., 2019
Universal Regularization Methods: Varying the Power, the Smoothness and the Accuracy.
SIAM J. Optim., 2019
Optimality of orders one to three and beyond: Characterization and evaluation complexity in constrained nonconvex optimization.
J. Complex., 2019
2018
Global convergence rate analysis of unconstrained optimization methods based on probabilistic models.
Math. Program., 2018
Second-Order Optimality and Beyond: Characterization and Evaluation Complexity in Convexly Constrained Nonlinear Optimization.
Found. Comput. Math., 2018
Proceedings of the IEEE International Symposium on Circuits and Systems, 2018
2017
IEEE Trans. Inf. Theory, 2017
Worst-case evaluation complexity of regularization methods for smooth unconstrained optimization using Hölder continuous gradients.
Optim. Methods Softw., 2017
Corrigendum: On the complexity of finding first-order critical points in constrained nonlinear optimization.
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
2016
Comput. Optim. Appl., 2016
2015
A New and Improved Quantitative Recovery Analysis for Iterative Hard Thresholding Algorithms in Compressed Sensing.
IEEE Trans. Inf. Theory, 2015
On the Evaluation Complexity of Constrained Nonlinear Least-Squares and General Constrained Nonlinear Optimization Using Second-Order Methods.
SIAM J. Numer. Anal., 2015
Branching and bounding improvements for global optimization algorithms with Lipschitz continuity properties.
J. Glob. Optim., 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
A note about the complexity of minimizing Nesterov's smooth Chebyshev-Rosenbrock function.
Optim. Methods Softw., 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
J. Complex., 2012
2011
On the Evaluation Complexity of Composite Function Minimization with Applications to Nonconvex Nonlinear Programming.
SIAM J. Optim., 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
2010
Convergence of a Regularized Euclidean Residual Algorithm for Nonlinear Least-Squares.
SIAM J. Numer. Anal., 2010
On the Complexity of Steepest Descent, Newton's and Regularized Newton's Methods for Nonconvex Unconstrained Optimization Problems.
SIAM J. Optim., 2010
2009