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Richard H. Byrd
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2020 – today
- 2023
- [j49]Figen Öztoprak, Richard H. Byrd, Jorge Nocedal:
Constrained Optimization in the Presence of Noise. SIAM J. Optim. 33(3): 2118-2136 (2023) - 2022
- [j48]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) - 2020
- [j47]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
- [j46]Albert S. Berahas
, Richard H. Byrd, Jorge Nocedal:
Derivative-Free Optimization of Noisy Functions via Quasi-Newton Methods. SIAM J. Optim. 29(2): 965-993 (2019) - [j45]Paul T. Boggs, Richard H. Byrd:
Adaptive, Limited-Memory BFGS Algorithms for Unconstrained Optimization. SIAM J. Optim. 29(2): 1282-1299 (2019) - [j44]Richard H. Byrd, Jorio Cocola, Richard A. Tapia:
Extending the Pennisi-McCormick Second-Order Sufficiency Theory for Nonlinear Programming to Infinite Dimensions. SIAM J. Optim. 29(3): 1870-1878 (2019) - 2018
- [j43]Raghu Bollapragada, Richard H. Byrd, Jorge Nocedal:
Adaptive Sampling Strategies for Stochastic Optimization. SIAM J. Optim. 28(4): 3312-3343 (2018) - 2016
- [j42]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) - [j41]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) - [j40]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) - 2015
- [j39]Stefan Solntsev
An algorithm for quadratic ℓ1-regularized optimization with a flexible active-set strategy. Optim. Methods Softw. 30(6): 1213-1237 (2015) - 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
- [j38]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) - 2012
- [j37]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) - [j36]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) - 2011
- [j35]Richard H. Byrd, Richard A. Waltz:
An active-set algorithm for nonlinear programming using parametric linear programming. Optim. Methods Softw. 26(1): 47-66 (2011) - [j34]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) - 2010
- [j33]Richard H. Byrd, Frank E. Curtis
An inexact Newton method for nonconvex equality constrained optimization. Math. Program. 122(2): 273-299 (2010) - [j32]Richard H. Byrd, Frank E. Curtis
Infeasibility Detection and SQP Methods for Nonlinear Optimization. SIAM J. Optim. 20(5): 2281-2299 (2010)
2000 – 2009
- 2008
- [j31]Richard H. Byrd, Jorge Nocedal, Richard A. Waltz:
Steering exact penalty methods for nonlinear programming. Optim. Methods Softw. 23(2): 197-213 (2008) - [j30]Richard H. Byrd, Frank E. Curtis
An Inexact SQP Method for Equality Constrained Optimization. SIAM J. Optim. 19(1): 351-369 (2008) - 2006
- [j29]Ernesto E. Prudencio, Richard H. Byrd, Xiao-Chuan Cai:
Parallel Full Space SQP Lagrange-Newton-Krylov-Schwarz Algorithms for PDE-Constrained Optimization Problems. SIAM J. Sci. Comput. 27(4): 1305-1328 (2006) - 2005
- [j28]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
- [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) - [j25]Elizabeth Eskow, Brett W. Bader, Richard H. Byrd, Silvia N. Crivelli, Teresa Head-Gordon, Vincent Lamberti, Robert B. Schnabel:
An optimization approach to the problem of protein structure prediction. Math. Program. 101(3): 497-514 (2004) - [c6]Ernesto E. Prudencio, Richard H. Byrd, Xiao-Chuan Cai:
Domain Decomposition Methods for PDE Constrained Optimization Problems. VECPAR 2004: 569-582 - 2003
- [j24]Richard H. Byrd, Jorge Nocedal, Richard A. Waltz:
Feasible Interior Methods Using Slacks for Nonlinear Optimization. Comput. Optim. Appl. 26(1): 35-61 (2003) - 2000
- [j23]Silvia N. Crivelli, Richard H. Byrd, Elizabeth Eskow, Robert B. Schnabel, Richard Yu, Thomas M. Philip, Teresa Head-Gordon:
A Global Optimization Strategy for Predicting -helical Protein Tertiary Structure. Comput. Chem. 24(3-4): 489-497 (2000) - [j22]Chung-Shang Shao, Richard H. Byrd, Elizabeth Eskow, Robert B. Schnabel:
Global Optimization For Molecular Clusters Using A New Smoothing Approach. J. Glob. Optim. 16(2): 167-196 (2000) - [j21]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)
1990 – 1999
- 1999
- [j20]Yuanfu Xie, Richard H. Byrd:
Practical Update Criteria for Reduced Hessian SQP: Global Analysis. SIAM J. Optim. 9(3): 578-604 (1999) - [j19]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) - [c5]Silvia N. Crivelli, Teresa Head-Gordon, Richard H. Byrd, Elizabeth Eskow, Robert B. Schnabel:
A Hierarchical Approach for Parallelization of a Global Optimization Method for Protein Structure Prediction. Euro-Par 1999: 578-585 - 1997
- [j18]Zhihong Zou, Richard H. Byrd, Robert B. Schnabel:
A Stochastic/Perturbation Global Optimization Algorithm for Distance Geometry Problems. J. Glob. Optim. 11(1): 91-105 (1997) - [j17]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) - 1996
- [j16]Richard H. Byrd, Humaid Khalfan, Robert B. Schnabel:
Analysis of a Symmetric Rank-One Trust Region Method. SIAM J. Optim. 6(4): 1025-1039 (1996) - 1995
- [j15]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) - [c4]Richard H. Byrd, Elizabeth Eskow, André van der Hoek, Robert B. Schnabel, Chung-Shang Shao, Zhihong Zou:
Global optimization methods for protein folding problems. Global Minimization of Nonconvex Energy Functions: Molecular Conformation and Protein Folding 1995: 29-39 - [c3]Richard H. Byrd, Elizabeth Eskow, André van der Hoek, Robert B. Schnabel, Klaas P. B. Oldenkamp:
A Parallel Global Optimization Method for Solving Molecular Cluster and Polymer Conformation Problems. PP 1995: 72-77 - 1994
- [j14]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
- [j13]Humaid Khalfan, Richard H. Byrd, Robert B. Schnabel:
A Theoretical and Experimental Study of the Symmetric Rank-One Update. SIAM J. Optim. 3(1): 1-24 (1993) - [c2]Richard H. Byrd, Thomas Derby, Elizabeth Eskow, Klaas P. B. Oldenkamp, Robert B. Schnabel, Christos Triantafillou:
Parallel Global Optimization Methods for Molecular Configuration Problems. PPSC 1993: 165-169 - 1992
- [j12]Richard H. Byrd, Richard A. Tapia, Yin Zhang:
An SQP Augmented Lagrangian BFGS Algorithm for Constrained Optimization. SIAM J. Optim. 2(2): 210-241 (1992) - [j11]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) - [j10]Xiaodong Zhang, Richard H. Byrd, Robert B. Schnabel:
Parallel Methods for Solving Nonlinear Block Bordered Systems of Equations. SIAM J. Sci. Comput. 13(4): 841-859 (1992) - 1991
- [j9]Richard H. Byrd, Jorge Nocedal:
An analysis of reduced Hessian methods for constrained optimization. Math. Program. 49: 285-323 (1991) - 1990
- [j8]Richard H. Byrd, Cornelius L. Dert, Alexander H. G. Rinnooy Kan, Robert B. Schnabel:
Concurrent Stochastic Methods for Global Optimization. Math. Program. 46: 1-29 (1990)
1980 – 1989
- 1989
- [j7]Paul T. Boggs, Janet R. Donaldson, Richard H. Byrd, Robert B. Schnabel:
Algorithm 676: ODRPACK: software for weighted orthogonal distance regression. ACM Trans. Math. Softw. 15(4): 348-364 (1989) - 1988
- [j6]Richard H. Byrd, Robert B. Schnabel, Gerald A. Shultz:
Approximate solution of the trust region problem by minimization over two-dimensional subspaces. Math. Program. 40(1-3): 247-263 (1988) - [j5]Richard H. Byrd, Robert B. Schnabel, Gerald A. Shultz:
Parallel quasi-Newton methods for unconstrained optimization. Math. Program. 42(1-3): 273-306 (1988) - 1987
- [j4]Richard H. Byrd, Alan J. Goldman, Miriam Heller:
Technical Note - Recognizing Unbounded Integer Programs. Oper. Res. 35(1): 140-142 (1987) - 1986
- [j3]Richard H. Byrd, Robert B. Schnabel:
Continuity of the null space basis and constrained optimization. Math. Program. 35(1): 32-41 (1986) - 1985
- [j2]Richard H. Byrd:
An example of irregular convergence in some constrained optimization methods that use the projected hessian. Math. Program. 32(2): 232-237 (1985) - 1984
- [c1]Michael R. Lightner, Gary D. Hachtel, Richard H. Byrd, Michel Heydemann:
A Theory and Algorithmic Frame for Switch Level Simulation. IMACS European Simulation Meeting 1984: 151-159
1970 – 1979
- 1975
- [j1]Richard H. Byrd, Richard A. Tapia:
An extension of Curry's theorem to steepest descent in normed linear spaces. Math. Program. 9(1): 247-254 (1975)
Coauthor Index
aka: Robert B. Schnabel
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