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Jorge Nocedal
Person information
- affiliation: Northwestern University, Illinois, USA
- award (2017): John von Neumann Theory Prize
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2020 – today
- 2024
- [i7]Yuchen Lou, Shigeng Sun, Jorge Nocedal:
Noise-Tolerant Optimization Methods for the Solution of a Robust Design Problem. CoRR abs/2401.15007 (2024) - 2023
- [j64]Shigeng Sun, Jorge Nocedal
:
A trust region method for noisy unconstrained optimization. Math. Program. 202(1): 445-472 (2023) - [j63]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): 289-311 (2023) - [j62]Figen Öztoprak, Richard H. Byrd, Jorge Nocedal:
Constrained Optimization in the Presence of Noise. SIAM J. Optim. 33(3): 2118-2136 (2023) - 2022
- [j61]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): 29-55 (2022) - [j60]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): 2302- (2022) - 2020
- [j59]Albert S. Berahas
An investigation of Newton-Sketch and subsampled Newton methods. Optim. Methods Softw. 35(4): 661-680 (2020) - [j58]Yuchen Xie, Richard H. Byrd, Jorge Nocedal:
Analysis of the BFGS Method with Errors. SIAM J. Optim. 30(1): 182-209 (2020)
2010 – 2019
- 2019
- [j57]Albert S. Berahas
Derivative-Free Optimization of Noisy Functions via Quasi-Newton Methods. SIAM J. Optim. 29(2): 965-993 (2019) - 2018
- [j56]Raghu Bollapragada, Richard H. Byrd, Jorge Nocedal:
Adaptive Sampling Strategies for Stochastic Optimization. SIAM J. Optim. 28(4): 3312-3343 (2018) - [j55]Léon Bottou, Frank E. Curtis
Optimization Methods for Large-Scale Machine Learning. SIAM Rev. 60(2): 223-311 (2018) - [c8]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: 619-628 - [i6]Raghu Bollapragada, Dheevatsa Mudigere, Jorge Nocedal, Hao-Jun Michael Shi, Ping Tak Peter Tang:
A Progressive Batching L-BFGS Method for Machine Learning. CoRR abs/1802.05374 (2018) - 2017
- [c7]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 - [i5]Albert S. Berahas, Raghu Bollapragada, Jorge Nocedal:
An Investigation of Newton-Sketch and Subsampled Newton Methods. CoRR abs/1705.06211 (2017) - 2016
- [j54]Richard H. Byrd, Jorge Nocedal, Figen Öztoprak:
An inexact successive quadratic approximation method for L-1 regularized optimization. Math. Program. 157(2): 375-396 (2016) - [j53]Richard H. Byrd, Gillian M. Chin, Jorge Nocedal, Figen Öztoprak:
A family of second-order methods for convex ℓ1-regularized optimization. Math. Program. 159(1-2): 435-467 (2016) - [j52]Nitish Shirish Keskar, Jorge Nocedal, Figen Öztoprak, Andreas Wächter:
A second-order method for convex l1-regularized optimization with active-set prediction. Optim. Methods Softw. 31(3): 605-621 (2016) - [j51]Richard H. Byrd, S. L. Hansen, Jorge Nocedal, Yoram Singer:
A Stochastic Quasi-Newton Method for Large-Scale Optimization. SIAM J. Optim. 26(2): 1008-1031 (2016) - [c6]Albert S. Berahas, Jorge Nocedal, Martin Takác:
A Multi-Batch L-BFGS Method for Machine Learning. NIPS 2016: 1055-1063 - [i4]Albert S. Berahas, Jorge Nocedal, Martin Takác:
A Multi-Batch L-BFGS Method for Machine Learning. CoRR abs/1605.06049 (2016) - [i3]Léon Bottou, Frank E. Curtis, Jorge Nocedal:
Optimization Methods for Large-Scale Machine Learning. CoRR abs/1606.04838 (2016) - [i2]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 abs/1609.04836 (2016) - 2015
- [j50]Stefan Solntsev
An algorithm for quadratic ℓ1-regularized optimization with a flexible active-set strategy. Optim. Methods Softw. 30(6): 1213-1237 (2015) - 2014
- [j49]Jorge Nocedal, Figen Öztoprak, Richard A. Waltz:
An interior point method for nonlinear programming with infeasibility detection capabilities. Optim. Methods Softw. 29(4): 837-854 (2014) - [i1]Richard H. Byrd, S. L. Hansen, Jorge Nocedal, Yoram Singer:
A Stochastic Quasi-Newton Method for Large-Scale Optimization. CoRR abs/1401.7020 (2014) - 2013
- [j48]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): 289-324 (2013) - [j47]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): 1371-1397 (2013) - [j46]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): 2244-2254 (2013) - 2012
- [j45]Richard H. Byrd, Gabriel López-Calva, Jorge Nocedal:
A line search exact penalty method using steering rules. Math. Program. 133(1-2): 39-73 (2012) - [j44]Richard H. Byrd, Gillian M. Chin, Jorge Nocedal, Yuchen Wu:
Sample size selection in optimization methods for machine learning. Math. Program. 134(1): 127-155 (2012) - [c5]Samantha Hansen, Jorge Nocedal:
Second-order methods for L1 regularized problems in machine learning. ICASSP 2012: 5237-5240 - [c4]Peder A. Olsen, Figen Öztoprak, Jorge Nocedal, Steven J. Rennie:
Newton-Like Methods for Sparse Inverse Covariance Estimation. NIPS 2012: 764-772 - 2011
- [j43]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): 813-825 (2011) - [j42]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): 977-995 (2011) - [j41]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): 7:1-7:4 (2011) - 2010
- [j40]Richard H. Byrd, Frank E. Curtis
An inexact Newton method for nonconvex equality constrained optimization. Math. Program. 122(2): 273-299 (2010) - [j39]Richard H. Byrd, Frank E. Curtis
Infeasibility Detection and SQP Methods for Nonlinear Optimization. SIAM J. Optim. 20(5): 2281-2299 (2010)
2000 – 2009
- 2009
- [j38]Giovanni Fasano
On the geometry phase in model-based algorithms for derivative-free optimization. Optim. Methods Softw. 24(1): 145-154 (2009) - [j37]Jorge Nocedal, Andreas Wächter, Richard A. Waltz:
Adaptive Barrier Update Strategies for Nonlinear Interior Methods. SIAM J. Optim. 19(4): 1674-1693 (2009) - [j36]Frank E. Curtis
A Matrix-Free Algorithm for Equality Constrained Optimization Problems with Rank-Deficient Jacobians. SIAM J. Optim. 20(3): 1224-1249 (2009) - [c3]Jorge Nocedal:
Fast and parallel algorithms for pricing American options: keynote. SC-WHPCF 2009 - 2008
- [j35]José Luis Morales, Jorge Nocedal, Mikhail Smelyanskiy:
An algorithm for the fast solution of symmetric linear complementarity problems. Numerische Mathematik 111(2): 251-266 (2008) - [j34]Richard H. Byrd, Jorge Nocedal, Richard A. Waltz:
Steering exact penalty methods for nonlinear programming. Optim. Methods Softw. 23(2): 197-213 (2008) - [j33]Richard H. Byrd, Frank E. Curtis
An Inexact SQP Method for Equality Constrained Optimization. SIAM J. Optim. 19(1): 351-369 (2008) - 2007
- [j32]Frank E. Curtis, Jorge Nocedal:
Steplength selection in interior-point methods for quadratic programming. Appl. Math. Lett. 20(5): 516-523 (2007) - 2006
- [j31]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): 391-408 (2006) - [j30]Sven Leyffer
Interior Methods for Mathematical Programs with Complementarity Constraints. SIAM J. Optim. 17(1): 52-77 (2006) - [c2]Long Hei, Jorge Nocedal, Richard A. Waltz:
A Numerical Study of Active-Set and Interior-Point Methods for Bound Constrained Optimization. HPSC 2006: 273-292 - 2005
- [j29]Richard H. Byrd, Nicholas I. M. Gould
On the Convergence of Successive Linear-Quadratic Programming Algorithms. SIAM J. Optim. 16(2): 471-489 (2005) - 2004
- [j28]E. Michael Gertz, Jorge Nocedal, Annick Sartenaer:
A starting point strategy for nonlinear interior methods. Appl. Math. Lett. 17(8): 945-952 (2004) - [j27]Richard H. Byrd, Marcelo Marazzi, Jorge Nocedal:
On the convergence of Newton iterations to non-stationary points. Math. Program. 99(1): 127-148 (2004) - [j26]Richard H. Byrd, Nicholas I. M. Gould
An algorithm for nonlinear optimization using linear programming and equality constrained subproblems. Math. Program. 100(1): 27-48 (2004) - 2003
- [j25]Richard H. Byrd, Jorge Nocedal, Richard A. Waltz:
Feasible Interior Methods Using Slacks for Nonlinear Optimization. Comput. Optim. Appl. 26(1): 35-61 (2003) - [c1]Jorge Nocedal:
Solving Optimization Problems Using Parallel and Grid Computing. ENC 2003: 6 - 2002
- [j24]José Luis Morales, Jorge Nocedal:
Enriched Methods for Large-Scale Unconstrained Optimization. Comput. Optim. Appl. 21(2): 143-154 (2002) - [j23]Jorge Nocedal, Annick Sartenaer, Ciyou Zhu:
On the Behavior of the Gradient Norm in the Steepest Descent Method. Comput. Optim. Appl. 22(1): 5-35 (2002) - [j22]Marcelo Marazzi, Jorge Nocedal:
Wedge trust region methods for derivative free optimization. Math. Program. 91(2): 289-305 (2002) - 2001
- [j21]Nicholas I. M. Gould
On the Solution of Equality Constrained Quadratic Programming Problems Arising in Optimization. SIAM J. Sci. Comput. 23(4): 1376-1395 (2001) - [j20]José Luis Morales, Jorge Nocedal:
Algorithm 809: PREQN: Fortran 77 subroutines for preconditioning the conjugate gradient method. ACM Trans. Math. Softw. 27(1): 83-91 (2001) - 2000
- [j19]Lorenz T. Biegler
Numerical Experience with a Reduced Hessian Method for Large Scale Constrained Optimization. Comput. Optim. Appl. 15(1): 45-67 (2000) - [j18]Richard H. Byrd, Jean Charles Gilbert
A trust region method based on interior point techniques for nonlinear programming. Math. Program. 89(1): 149-185 (2000) - [j17]José Luis Morales, Jorge Nocedal:
Automatic Preconditioning by Limited Memory Quasi-Newton Updating. SIAM J. Optim. 10(4): 1079-1096 (2000)
1990 – 1999
- 1999
- [b1]Jorge Nocedal, Stephen J. Wright:
Numerical Optimization. Springer 1999, ISBN 978-0-387-98793-4, pp. 1-634 - [j16]Richard H. Byrd, Mary E. Hribar, Jorge Nocedal:
An Interior Point Algorithm for Large-Scale Nonlinear Programming. SIAM J. Optim. 9(4): 877-900 (1999) - 1998
- [j15]Marucha Lalee, Jorge Nocedal, Todd D. Plantenga:
On the Implementation of an Algorithm for Large-Scale Equality Constrained Optimization. SIAM J. Optim. 8(3): 682-706 (1998) - 1997
- [j14]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): 550-560 (1997) - 1995
- [j13]Lorenz T. Biegler
A Reduced Hessian Method for Large-Scale Constrained Optimization. SIAM J. Optim. 5(2): 314-347 (1995) - [j12]Richard H. Byrd, Peihuang Lu, Jorge Nocedal, Ciyou Zhu:
A Limited Memory Algorithm for Bound Constrained Optimization. SIAM J. Sci. Comput. 16(5): 1190-1208 (1995) - 1994
- [j11]Richard H. Byrd, Jorge Nocedal, Robert B. Schnabel:
Representations of quasi-Newton matrices and their use in limited memory methods. Math. Program. 63: 129-156 (1994) - 1993
- [j10]Jorge Nocedal, Ya-Xiang Yuan:
Analysis of a self-scaling quasi-Newton method. Math. Program. 61: 19-37 (1993) - [j9]Marucha Lalee, Jorge Nocedal:
Automatic Column Scaling Strategies for Quasi-Newton Methods. SIAM J. Optim. 3(3): 637-653 (1993) - 1992
- [j8]Jean Charles Gilbert
Global Convergence Properties of Conjugate Gradient Methods for Optimization. SIAM J. Optim. 2(1): 21-42 (1992) - [j7]Richard H. Byrd, Dong C. Liu, Jorge Nocedal:
On the Behavior of Broyden's Class of Quasi-Newton Methods. SIAM J. Optim. 2(4): 533-557 (1992) - 1991
- [j6]Richard H. Byrd, Jorge Nocedal:
An analysis of reduced Hessian methods for constrained optimization. Math. Program. 49: 285-323 (1991) - [j5]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): 358-372 (1991)
1980 – 1989
- 1989
- [j4]Dong C. Liu, Jorge Nocedal:
On the limited memory BFGS method for large scale optimization. Math. Program. 45(1-3): 503-528 (1989) - 1985
- [j3]William C. Davidon, Jorge Nocedal:
Evaluation of Step Directions in Optimization Algorithms. ACM Trans. Math. Softw. 11(1): 12-19 (1985) - 1982
- [j2]Larry Nazareth, Jorge Nocedal:
Conjugate direction methods with variable storage. Math. Program. 23(1): 326-340 (1982)
1970 – 1979
- 1979
- [j1]Petter Bjørstad, Jorge Nocedal:
Analysis of a new algorithm for one-dimensional minimization. Computing 22(1): 93-100 (1979)
Coauthor Index
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