Jorge Nocedal

Publication Activity (10 Years)

Years Active: 1979-2024
Publications (10 Years): 23

Top Topics

Constrained Optimization

Nonlinear Programming

Optimization Method

Top Venues

Optim. Methods Softw.

Publications

Yuchen Lou, Shigeng Sun, Jorge Nocedal
Noise-Tolerant Optimization Methods for the Solution of a Robust Design Problem. CoRR (2024)
Hao-Jun Michael Shi, Melody Qiming Xuan, Figen Öztoprak, Jorge Nocedal
On the numerical performance of finite-difference-based methods for derivative-free optimization. Optim. Methods Softw. 38 (2) (2023)
Figen Öztoprak, Richard H. Byrd, Jorge Nocedal
Constrained Optimization in the Presence of Noise. SIAM J. Optim. 33 (3) (2023)
Shigeng Sun, Jorge Nocedal
A trust region method for noisy unconstrained optimization. Math. Program. 202 (1) (2023)
Hao-Jun Michael Shi, Yuchen Xie, Richard H. Byrd, Jorge Nocedal
A Noise-Tolerant Quasi-Newton Algorithm for Unconstrained Optimization. SIAM J. Optim. 32 (1) (2022)
Hao-Jun Michael Shi, Yuchen Xie, Melody Qiming Xuan, Jorge Nocedal
Adaptive Finite-Difference Interval Estimation for Noisy Derivative-Free Optimization. SIAM J. Sci. Comput. 44 (4) (2022)
Yuchen Xie, Richard H. Byrd, Jorge Nocedal
Analysis of the BFGS Method with Errors. SIAM J. Optim. 30 (1) (2020)
Albert S. Berahas, Raghu Bollapragada, Jorge Nocedal
An investigation of Newton-Sketch and subsampled Newton methods. Optim. Methods Softw. 35 (4) (2020)
Albert S. Berahas, Richard H. Byrd, Jorge Nocedal
Derivative-Free Optimization of Noisy Functions via Quasi-Newton Methods. SIAM J. Optim. 29 (2) (2019)
Léon Bottou, Frank E. Curtis, Jorge Nocedal
Optimization Methods for Large-Scale Machine Learning. SIAM Rev. 60 (2) (2018)
Raghu Bollapragada, Dheevatsa Mudigere, Jorge Nocedal, Hao-Jun Michael Shi, Ping Tak Peter Tang
A Progressive Batching L-BFGS Method for Machine Learning. CoRR (2018)
Raghu Bollapragada, Richard H. Byrd, Jorge Nocedal
Adaptive Sampling Strategies for Stochastic Optimization. SIAM J. Optim. 28 (4) (2018)
Raghu Bollapragada, Dheevatsa Mudigere, Jorge Nocedal, Hao-Jun Michael Shi, Ping Tak Peter Tang
A Progressive Batching L-BFGS Method for Machine Learning. ICML (2018)
Nitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, Ping Tak Peter Tang
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima. ICLR (2017)
Albert S. Berahas, Raghu Bollapragada, Jorge Nocedal
An Investigation of Newton-Sketch and Subsampled Newton Methods. CoRR (2017)
Albert S. Berahas, Jorge Nocedal, Martin Takác
A Multi-Batch L-BFGS Method for Machine Learning. NIPS (2016)
Nitish Shirish Keskar, Jorge Nocedal, Figen Öztoprak, Andreas Wächter
-regularized optimization with active-set prediction. Optim. Methods Softw. 31 (3) (2016)
Albert S. Berahas, Jorge Nocedal, Martin Takác
A Multi-Batch L-BFGS Method for Machine Learning. CoRR (2016)
Richard H. Byrd, Jorge Nocedal, Figen Öztoprak
An inexact successive quadratic approximation method for L-1 regularized optimization. Math. Program. 157 (2) (2016)
Nitish Shirish Keskar, Dheevatsa Mudigere, Jorge Nocedal, Mikhail Smelyanskiy, Ping Tak Peter Tang
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima. CoRR (2016)
Léon Bottou, Frank E. Curtis, Jorge Nocedal
Optimization Methods for Large-Scale Machine Learning. CoRR (2016)
Richard H. Byrd, S. L. Hansen, Jorge Nocedal, Yoram Singer
A Stochastic Quasi-Newton Method for Large-Scale Optimization. SIAM J. Optim. 26 (2) (2016)
Richard H. Byrd, Gillian M. Chin, Jorge Nocedal, Figen Öztoprak
-regularized optimization. Math. Program. 159 (1-2) (2016)
Stefan Solntsev, Jorge Nocedal, Richard H. Byrd
-regularized optimization with a flexible active-set strategy. Optim. Methods Softw. 30 (6) (2015)
Richard H. Byrd, S. L. Hansen, Jorge Nocedal, Yoram Singer
A Stochastic Quasi-Newton Method for Large-Scale Optimization. CoRR (2014)
Jorge Nocedal, Figen Öztoprak, Richard A. Waltz
An interior point method for nonlinear programming with infeasibility detection capabilities. Optim. Methods Softw. 29 (4) (2014)
Daniel P. Robinson, Liming Feng, Jorge Nocedal, Jong-Shi Pang
Subspace Accelerated Matrix Splitting Algorithms for Asymmetric and Symmetric Linear Complementarity Problems. SIAM J. Optim. 23 (3) (2013)
Gillian M. Chin, Jorge Nocedal, Peder A. Olsen, Steven J. Rennie
Second Order Methods for Optimizing Convex Matrix Functions and Sparse Covariance Clustering. IEEE Trans. Speech Audio Process. 21 (11) (2013)
Richard H. Byrd, Jorge Nocedal, Richard A. Waltz, Yuchen Wu
On the use of piecewise linear models in nonlinear programming. Math. Program. 137 (1-2) (2013)
Richard H. Byrd, Gillian M. Chin, Jorge Nocedal, Yuchen Wu
Sample size selection in optimization methods for machine learning. Math. Program. 134 (1) (2012)
Samantha Hansen, Jorge Nocedal
Second-order methods for L1 regularized problems in machine learning. ICASSP (2012)
Peder A. Olsen, Figen Öztoprak, Jorge Nocedal, Steven J. Rennie
Newton-Like Methods for Sparse Inverse Covariance Estimation. NIPS (2012)
Richard H. Byrd, Gabriel López-Calva, Jorge Nocedal
A line search exact penalty method using steering rules. Math. Program. 133 (1-2) (2012)
Richard H. Byrd, Gillian M. Chin, Will Neveitt, Jorge Nocedal
On the Use of Stochastic Hessian Information in Optimization Methods for Machine Learning. SIAM J. Optim. 21 (3) (2011)
José Luis Morales, Jorge Nocedal
Remark on "algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound constrained optimization". ACM Trans. Math. Softw. 38 (1) (2011)
Liming Feng, Vadim Linetsky, José Luis Morales, Jorge Nocedal
On the solution of complementarity problems arising in American options pricing. Optim. Methods Softw. 26 (4-5) (2011)
Richard H. Byrd, Frank E. Curtis, Jorge Nocedal
Infeasibility Detection and SQP Methods for Nonlinear Optimization. SIAM J. Optim. 20 (5) (2010)
Richard H. Byrd, Frank E. Curtis, Jorge Nocedal
An inexact Newton method for nonconvex equality constrained optimization. Math. Program. 122 (2) (2010)
Giovanni Fasano, José Luis Morales, Jorge Nocedal
On the geometry phase in model-based algorithms for derivative-free optimization. Optim. Methods Softw. 24 (1) (2009)
Jorge Nocedal
Fast and parallel algorithms for pricing American options: keynote. SC-WHPCF (2009)
Frank E. Curtis, Jorge Nocedal, Andreas Wächter
A Matrix-Free Algorithm for Equality Constrained Optimization Problems with Rank-Deficient Jacobians. SIAM J. Optim. 20 (3) (2009)
Jorge Nocedal, Andreas Wächter, Richard A. Waltz
Adaptive Barrier Update Strategies for Nonlinear Interior Methods. SIAM J. Optim. 19 (4) (2009)
Richard H. Byrd, Jorge Nocedal, Richard A. Waltz
Steering exact penalty methods for nonlinear programming. Optim. Methods Softw. 23 (2) (2008)
José Luis Morales, Jorge Nocedal, Mikhail Smelyanskiy
An algorithm for the fast solution of symmetric linear complementarity problems. Numerische Mathematik 111 (2) (2008)
Richard H. Byrd, Frank E. Curtis, Jorge Nocedal
An Inexact SQP Method for Equality Constrained Optimization. SIAM J. Optim. 19 (1) (2008)
Frank E. Curtis, Jorge Nocedal
Steplength selection in interior-point methods for quadratic programming. Appl. Math. Lett. 20 (5) (2007)
Long Hei, Jorge Nocedal, Richard A. Waltz
A Numerical Study of Active-Set and Interior-Point Methods for Bound Constrained Optimization. HPSC (2006)
Sven Leyffer, Gabriel López-Calva, Jorge Nocedal
Interior Methods for Mathematical Programs with Complementarity Constraints. SIAM J. Optim. 17 (1) (2006)
Richard A. Waltz, José Luis Morales, Jorge Nocedal, Dominique Orban
An interior algorithm for nonlinear optimization that combines line search and trust region steps. Math. Program. 107 (3) (2006)
Richard H. Byrd, Nicholas I. M. Gould, Jorge Nocedal, Richard A. Waltz
On the Convergence of Successive Linear-Quadratic Programming Algorithms. SIAM J. Optim. 16 (2) (2005)
Richard H. Byrd, Nicholas I. M. Gould, Jorge Nocedal, Richard A. Waltz
An algorithm for nonlinear optimization using linear programming and equality constrained subproblems. Math. Program. 100 (1) (2004)
Richard H. Byrd, Marcelo Marazzi, Jorge Nocedal
On the convergence of Newton iterations to non-stationary points. Math. Program. 99 (1) (2004)
E. Michael Gertz, Jorge Nocedal, Annick Sartenaer
A starting point strategy for nonlinear interior methods. Appl. Math. Lett. 17 (8) (2004)
Jorge Nocedal
Solving Optimization Problems Using Parallel and Grid Computing. ENC (2003)
Richard H. Byrd, Jorge Nocedal, Richard A. Waltz
Feasible Interior Methods Using Slacks for Nonlinear Optimization. Comput. Optim. Appl. 26 (1) (2003)
Marcelo Marazzi, Jorge Nocedal
Wedge trust region methods for derivative free optimization. Math. Program. 91 (2) (2002)
Jorge Nocedal, Annick Sartenaer, Ciyou Zhu
On the Behavior of the Gradient Norm in the Steepest Descent Method. Comput. Optim. Appl. 22 (1) (2002)
José Luis Morales, Jorge Nocedal
Enriched Methods for Large-Scale Unconstrained Optimization. Comput. Optim. Appl. 21 (2) (2002)
Nicholas I. M. Gould, Mary E. Hribar, Jorge Nocedal
On the Solution of Equality Constrained Quadratic Programming Problems Arising in Optimization. SIAM J. Sci. Comput. 23 (4) (2001)
José Luis Morales, Jorge Nocedal
Algorithm 809: PREQN: Fortran 77 subroutines for preconditioning the conjugate gradient method. ACM Trans. Math. Softw. 27 (1) (2001)
José Luis Morales, Jorge Nocedal
Automatic Preconditioning by Limited Memory Quasi-Newton Updating. SIAM J. Optim. 10 (4) (2000)
Richard H. Byrd, Jean Charles Gilbert, Jorge Nocedal
A trust region method based on interior point techniques for nonlinear programming. Math. Program. 89 (1) (2000)
Lorenz T. Biegler, Jorge Nocedal, Claudia Schmid, David Ternet
Numerical Experience with a Reduced Hessian Method for Large Scale Constrained Optimization. Comput. Optim. Appl. 15 (1) (2000)
Richard H. Byrd, Mary E. Hribar, Jorge Nocedal
An Interior Point Algorithm for Large-Scale Nonlinear Programming. SIAM J. Optim. 9 (4) (1999)
Marucha Lalee, Jorge Nocedal, Todd D. Plantenga
On the Implementation of an Algorithm for Large-Scale Equality Constrained Optimization. SIAM J. Optim. 8 (3) (1998)
Ciyou Zhu, Richard H. Byrd, Peihuang Lu, Jorge Nocedal
Algorithm 778: L-BFGS-B: Fortran Subroutines for Large-Scale Bound-Constrained Optimization. ACM Trans. Math. Softw. 23 (4) (1997)
Lorenz T. Biegler, Jorge Nocedal, Claudia Schmid
A Reduced Hessian Method for Large-Scale Constrained Optimization. SIAM J. Optim. 5 (2) (1995)
Richard H. Byrd, Peihuang Lu, Jorge Nocedal, Ciyou Zhu
A Limited Memory Algorithm for Bound Constrained Optimization. SIAM J. Sci. Comput. 16 (5) (1995)
Richard H. Byrd, Jorge Nocedal, Robert B. Schnabel
Representations of quasi-Newton matrices and their use in limited memory methods. Math. Program. 63 (1994)
Jorge Nocedal, Ya-Xiang Yuan
Analysis of a self-scaling quasi-Newton method. Math. Program. 61 (1993)
Marucha Lalee, Jorge Nocedal
Automatic Column Scaling Strategies for Quasi-Newton Methods. SIAM J. Optim. 3 (3) (1993)
Richard H. Byrd, Dong C. Liu, Jorge Nocedal
On the Behavior of Broyden's Class of Quasi-Newton Methods. SIAM J. Optim. 2 (4) (1992)
Jean Charles Gilbert, Jorge Nocedal
Global Convergence Properties of Conjugate Gradient Methods for Optimization. SIAM J. Optim. 2 (1) (1992)
Richard H. Byrd, Jorge Nocedal
An analysis of reduced Hessian methods for constrained optimization. Math. Program. 49 (1991)
Stephen G. Nash, Jorge Nocedal
A Numerical Study of the Limited Memory BFGS Method and the Truncated-Newton Method for Large Scale Optimization. SIAM J. Optim. 1 (3) (1991)
Dong C. Liu, Jorge Nocedal
On the limited memory BFGS method for large scale optimization. Math. Program. 45 (1-3) (1989)
William C. Davidon, Jorge Nocedal
Evaluation of Step Directions in Optimization Algorithms. ACM Trans. Math. Softw. 11 (1) (1985)
Larry Nazareth, Jorge Nocedal
Conjugate direction methods with variable storage. Math. Program. 23 (1) (1982)
Petter Bjørstad, Jorge Nocedal
Analysis of a new algorithm for one-dimensional minimization. Computing 22 (1) (1979)