C. Cartis

发表

On the Complexity of Steepest Descent, Newton's and Regularized Newton's Methods for Nonconvex Unconstrained Optimization Problems

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2010, SIAM J. Optim..

Adaptive cubic overestimation methods for unconstrained optimization

P. Toint, N. Gould, C. Cartis, 2007 .

Adaptive cubic overestimation methods for unconstrained optimization. Part I: motivation, convergence and numerical results

P. Toint, N. Gould, C. Cartis, 2008 .

Adaptive cubic overestimation methods for unconstrained optimization . Part II : worst-case iteration complexity

P. Toint, N. Gould, C. Cartis, 2007 .

Trust-region and other regularisations of linear least-squares problems

P. Toint, N. Gould, C. Cartis, 2009 .

Erratum to: ``Global rates of convergence for nonconvex optimization on manifolds''

P. Absil, Nicolas Boumal, C. Cartis, 2016, IMA Journal of Numerical Analysis.

Optimal Newton-type methods for nonconvex smooth optimization problems

P. Toint, N. Gould, C. Cartis, 2011 .

Strong Evaluation Complexity of An Inexact Trust-Region Algorithm for Arbitrary-Order Unconstrained Nonconvex Optimization.

P. Toint, C. Cartis, N. Gould, 2020, 2011.00854.

THE RESTRICTED ISOMETRY PROPERTY AND ` Q-REGULARIZATION : PHASE TRANSITIONS FOR SPARSE APPROXIMATION

Jeffrey D. Blanchard, J. Tanner, C. Cartis, 2009 .

Some disadvantages of a Mehrotra-type primal-dual corrector interior point algorithm for linear programming

C. Cartis, 2009 .

On the Evaluation Complexity of Composite Function Minimization with Applications to Nonconvex Nonlinear Programming

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2011, SIAM J. Optim..

An adaptive cubic regularization algorithm for nonconvex optimization with convex constraints and its function-evaluation complexity

P. Toint, N. Gould, C. Cartis, 2012 .

Strong Evaluation Complexity Bounds for Arbitrary-Order Optimization of Nonconvex Nonsmooth Composite Functions

P. Toint, C. Cartis, Nick Gould, 2020, 2001.10802.

Adaptive cubic regularisation methods for unconstrained optimization. Part II: worst-case function- and derivative-evaluation complexity

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2011, Math. Program..

WORST-CASE EVALUATION COMPLEXITY AND OPTIMALITY OF SECOND-ORDER METHODS FOR NONCONVEX SMOOTH OPTIMIZATION

Philippe L. Toint, Coralia Cartis, Nick I. M. Gould, 2017, Proceedings of the International Congress of Mathematicians (ICM 2018).

Improved worst-case evaluation complexity for potentially rank-deficient nonlinear least-Euclidean-norm problems using higher-order regularized models

P. Toint, N. Gould, C. Cartis, 2015 .

Worst-case evaluation complexity of non-monotone gradient-related algorithms for unconstrained optimization

P. Toint, C. Cartis, P. Sampaio, 2015 .

Finding a point in the relative interior of a polyhedron

N. Gould, C. Cartis, 2007 .

Convergence Rate Analysis of a Stochastic Trust Region Method for Nonconvex Optimization

J. Blanchet, K. Scheinberg, C. Cartis, 2016 .

Second-Order Optimality and Beyond: Characterization and Evaluation Complexity in Convexly Constrained Nonlinear Optimization

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2018, Found. Comput. Math..

Evaluation complexity bounds for smooth constrained nonlinear optimisation using scaled KKT conditions, high-order models and the criticality measure $χ$ pdf

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2017, ArXiv.

Evaluation Complexity Bounds for Smooth Constrained Nonlinear Optimization Using Scaled KKT Conditions and High-Order Models

P. Toint, N. Gould, C. Cartis, 2019, Approximation and Optimization.

On the Evaluation Complexity of Cubic Regularization Methods for Potentially Rank-Deficient Nonlinear Least-Squares Problems and Its Relevance to Constrained Nonlinear Optimization

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2013, SIAM J. Optim..

Corrigendum: On the complexity of finding first-order critical points in constrained nonlinear optimization

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2017, Math. Program..

Adaptive cubic regularisation methods for unconstrained optimization. Part I: motivation, convergence and numerical results

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2011, Math. Program..

Can Top-of-Atmosphere Radiation Measurements Constrain Climate Predictions? Part II: Climate Sensitivity

C. Cartis, M. Mineter, S. Tett, 2013 .

Phase Transitions for Restricted Isometry Properties

Jeffrey D. Blanchard, J. Tanner, C. Cartis, 2009 .

COMPRESSED SENSING : HOW SHARP IS THE RIP ?

Jeffrey D. Blanchard, J. Tanner, C. Cartis, 2009 .

Convergence Rate Analysis of a Stochastic Trust-Region Method via Supermartingales

Katya Scheinberg, Jose Blanchet, Coralia Cartis, 2016, INFORMS Journal on Optimization.

A new perspective on the complexity of interior point methods for linear programming

Raphael A. Hauser, C. Cartis, Raphael A. Hauser, 2007 .

RAL-TR-2009-023 On the complexity of steepest descent , Newton ’ s method and regularized Newton methods for nonconvex unconstrained optimization

P. Toint, N. Gould, C. Cartis, 2009 .

RAL-TR-2008-005 Trust-region and other regularisations of linear least-squares problems

P. Toint, N. Gould, C. Cartis, 2008 .

Randomised subspace methods for non-convex optimization, with applications to nonlinear least-squares

C. Cartis, J. Fowkes, Zhen Shao, 2022, 2211.09873.

Corrigendum: On the complexity of finding first-order critical points in constrained nonlinear optimization

P. Toint, N. Gould, C. Cartis, 2016, Mathematical Programming.

RAL-TR-2007-007 Adaptive cubic overestimation methods for unconstrained optimization

P. Toint, N. Gould, C. Cartis, 2022 .

Nonlinear matrix recovery using optimization on the Grassmann manifold

C. Cartis, Armin Eftekhari, Florentin Goyens, 2021, ArXiv.

Branching and bounding improvements for global optimization algorithms with Lipschitz continuity properties

N. Gould, C. Cartis, J. Fowkes, 2014, Journal of Global Optimization.

Branching and bounding improvements for global optimization algorithms with Lipschitz continuity properties

Nicholas I. M. Gould, Jaroslav M. Fowkes, Coralia Cartis, 2014, Journal of Global Optimization.

Escaping local minima with local derivative-free methods: a numerical investigation

Coralia Cartis, Lindon Roberts, Oliver Sheridan-Methven, 2021, Optimization.

Scalable Derivative-Free Optimization for Nonlinear Least-Squares Problems pdf

Coralia Cartis, Lindon Roberts, Tyler Ferguson, 2020, ArXiv.

Improving the Flexibility and Robustness of Model-based Derivative-free Optimization Solvers

Coralia Cartis, Jan Fiala, Benjamin Marteau, 2018, ACM Trans. Math. Softw..

A derivative-free Gauss–Newton method

Coralia Cartis, Lindon Roberts, C. Cartis, 2017, Mathematical Programming Computation.

Escaping local minima with derivative-free methods: a numerical investigation

Coralia Cartis, Lindon Roberts, Oliver Sheridan-Methven, 2018 .

Can Top-of-Atmosphere Radiation Measurements Constrain Climate Predictions? Part I: Tuning

Coralia Cartis, Michael J. Mineter, Simon F. B. Tett, 2013 .

On the Oracle Complexity of First-Order and Derivative-Free Algorithms for Smooth Nonconvex Minimization

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2012, SIAM J. Optim..

Scalable subspace methods for derivative-free nonlinear least-squares optimization

C. Cartis, Lindon Roberts, 2021, Mathematical Programming.

Complexity bounds for second-order optimality in unconstrained optimization

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2012, J. Complex..

Global convergence rate analysis of unconstrained optimization methods based on probabilistic models

Katya Scheinberg, Coralia Cartis, K. Scheinberg, 2015, Mathematical Programming.

How much patience do you have? A worst-case perspective on smooth nonconvex optimization

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2012 .

Convergence of a Regularized Euclidean Residual Algorithm for Nonlinear Least-Squares

Nicholas I. M. Gould, Stefania Bellavia, Benedetta Morini, 2010, SIAM J. Numer. Anal..

Escaping local minima with local derivative-free methods: a numerical investigation

C. Cartis, O. Sheridan-Methven, Lindon Roberts, 2018, Optimization.

Quantitative Recovery Conditions for Tree-Based Compressed Sensing

Coralia Cartis, Andrew Thompson, C. Cartis, 2016, IEEE Transactions on Information Theory.

A New and Improved Quantitative Recovery Analysis for Iterative Hard Thresholding Algorithms in Compressed Sensing

Coralia Cartis, Andrew Thompson, C. Cartis, 2013, IEEE Transactions on Information Theory.

Explorer Compressed Sensing : How Sharp Is the Restricted Isometry Property ? pdf

Jared Tanner, Coralia Cartis, Jeffrey D. Blanchard, 2011 .

Phase Transitions for Greedy Sparse Approximation Algorithms pdf

Jared Tanner, Coralia Cartis, Andrew Thompson, 2010, ArXiv.

Evaluation complexity of adaptive cubic regularization methods for convex unconstrained optimization

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2012, Optim. Methods Softw..

Evaluation Complexity of Algorithms for Nonconvex Optimization: Theory, Computation and Perspectives

P. Toint, N. Gould, C. Cartis, 2022 .

Calibrating climate models using inverse methods: case studies with HadAM3, HadAM3P and HadCM3

Coralia Cartis, Michael J. Mineter, Simon F. B. Tett, 2017 .

A derivative-free optimisation method for global ocean biogeochemical models

Coralia Cartis, Samar Khatiwala, Iris Kriest, 2021, Geoscientific Model Development.

Adaptive regularization with cubics on manifolds

Nicolas Boumal, Naman Agarwal, Coralia Cartis, 2018, Mathematical Programming.

A dimensionality reduction technique for unconstrained global optimization of functions with low effective dimensionality

Coralia Cartis, Adilet Otemissov, C. Cartis, 2020, Information and Inference: A Journal of the IMA.

Convergent least-squares optimisation methods for variational data assimilation

Amos S. Lawless, Coralia Cartis, Nancy K. Nichols, 2021, 2107.12361.

Compressed Sensing: How Sharp Is the Restricted Isometry Property?

Jeffrey D. Blanchard, C. Cartis, Jared Tanner, 2010, SIAM Rev..

An Exact Tree Projection Algorithm for Wavelets

Coralia Cartis, Andrew Thompson, C. Cartis, 2013, IEEE Signal Processing Letters.

Global optimization using random embeddings pdf

Coralia Cartis, Estelle Massart, Adilet Otemissov, 2021, Mathematical Programming.

Bound-constrained global optimization of functions with low effective dimensionality using multiple random embeddings

Coralia Cartis, Estelle Massart, Adilet Otemissov, 2020, Mathematical Programming.

Optimality of orders one to three and beyond: characterization and evaluation complexity in constrained nonconvex optimization

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2017, J. Complex..

Sharp worst-case evaluation complexity bounds for arbitrary-order nonconvex optimization with inexpensive constraints

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2018, SIAM J. Optim..

Second-order optimality and beyond: characterization and evaluation complexity in nonconvex convexly-constrained optimization

Philippe L. Toint, Coralia Cartis, Nim Gould, 2016 .

Universal regularization methods - varying the power, the smoothness and the accuracy

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2018, 1811.07057.

On the Evaluation Complexity of Constrained Nonlinear Least-Squares and General Constrained Nonlinear Optimization Using Second-Order Methods

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2015, SIAM J. Numer. Anal..

On the complexity of finding first-order critical points in constrained nonlinear optimization

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2014, Math. Program..

A Randomised Subspace Gauss-Newton Method for Nonlinear Least-Squares

C. Cartis, J. Fowkes, Zhen Shao, 2022, ArXiv.

Hashing embeddings of optimal dimension, with applications to linear least squares pdf

Coralia Cartis, Jan Fiala, Zhen Shao, 2021, ArXiv.

Does Model Calibration Reduce Uncertainty in Climate Projections?

C. Cartis, S. Tett, N. Freychet, 2022, Journal of Climate.

Scalable subspace methods for derivative-free nonlinear least-squares optimization

Coralia Cartis, Lindon Roberts, C. Cartis, 2021, Mathematical Programming.

Convergence Rate Analysis of a Stochastic Trust Region Method via Submartingales

K. Scheinberg, C. Cartis, M. Menickelly, 2016 .

Convergence Rate Analysis of a Stochastic Trust-Region Method via Supermartingales

J. Blanchet, K. Scheinberg, C. Cartis, 2019, INFORMS Journal on Optimization.

A note about the complexity of minimizing Nesterov's smooth Chebyshev–Rosenbrock function

Nicholas I. M. Gould, Philippe L. Toint, Coralia Cartis, 2013, Optim. Methods Softw..

An adaptive cubic regularization algorithm for nonconvex optimization with convex constraints and its function-evaluation complexity

P. Toint, N. Gould, C. Cartis, 2012 .

Can Top-of-Atmosphere Radiation Measurements Constrain Climate Predictions? Part I: Tuning

Ping Liu, C. Cartis, M. Mineter, 2013 .

Can Top-of-Atmosphere Radiation Measurements Constrain Climate Predictions? Part II: Climate Sensitivity

C. Cartis, M. Mineter, S. Tett, 2013 .

Second-Order Optimality and Beyond: Characterization and Evaluation Complexity in Convexly Constrained Nonlinear Optimization

P. Toint, N. Gould, C. Cartis, 2017, Foundations of Computational Mathematics.

Decay Properties of Restricted Isometry Constants

Jared Tanner, Coralia Cartis, Jeffrey D. Blanchard, 2009, IEEE Signal Processing Letters.