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ORCIDYu-Hong Dai
Y. H. Dai
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- affiliation: Chinese Academy of Sciences, Institute of Computational Mathematics and Scientific Engineering Computing
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2020 – today
- 2024
[j84]Zhihua Allen-Zhao
, Fengmin Xu, Yu-Hong Dai, Sanyang Liu:
Robust enhanced indexation optimization with sparse industry layout constraint. Comput. Oper. Res. 161: 106420 (2024)- 2023
- [j83]Juan Gao, Xinwei Liu, Yu-Hong Dai, Yakui Huang, Junhua Gu:
Distributed stochastic gradient tracking methods with momentum acceleration for non-convex optimization. Comput. Optim. Appl. 84(2): 531-572 (2023) - [j82]Zhen-Yuan Ji, Yu-Hong Dai:
Greedy PSB methods with explicit superlinear convergence. Comput. Optim. Appl. 85(3): 753-786 (2023) - [j81]Liang Chen, Sheng-Jie Chen, Weikun Chen, Yu-Hong Dai, Tao Quan, Juan Chen:
Efficient presolving methods for solving maximal covering and partial set covering location problems. Eur. J. Oper. Res. 311(1): 73-87 (2023) - [j80]Fengmin Xu, Xuepeng Li, Yu-Hong Dai, Meihua Wang:
New insights and augmented Lagrangian algorithm for optimal portfolio liquidation with market impact. Int. Trans. Oper. Res. 30(5): 2640-2664 (2023) - [j79]Wei-Kun Chen, Liang Chen, Yu-Hong Dai:
Lifting for the integer knapsack cover polyhedron. J. Glob. Optim. 86(1): 205-249 (2023) - [j78]Jiawei Chen, Yu-Hong Dai:
Multiobjective optimization with least constraint violation: optimality conditions and exact penalization. J. Glob. Optim. 87(2): 807-830 (2023) - [j77]Rui-Jin Zhang, Xin-Wei Liu, Yu-Hong Dai:
IPRQP: a primal-dual interior-point relaxation algorithm for convex quadratic programming. J. Glob. Optim. 87(2): 1027-1053 (2023) - [j76]Yu-Hong Dai, Fangfang Xu, Liwei Zhang:
Alternating direction method of multipliers for linear hyperspectral unmixing. Math. Methods Oper. Res. 97(3): 289-310 (2023) - [j75]Yu-Hong Dai, Liwei Zhang:
The augmented Lagrangian method can approximately solve convex optimization with least constraint violation. Math. Program. 200(2): 633-667 (2023) - [j74]Sheng-Jie Chen, Weikun Chen, Yu-Hong Dai, Jian-Hua Yuan, Hou-Shan Zhang:
Efficient presolving methods for the influence maximization problem. Networks 82(3): 229-253 (2023) - [j73]Na Huang, Yu-Hong Dai, Dominique Orban, Michael A. Saunders:
Properties of semi-conjugate gradient methods for solving unsymmetric positive definite linear systems. Optim. Methods Softw. 38(5): 887-913 (2023) - [j72]Na Huang, Yu-Hong Dai, Dominique Orban, Michael A. Saunders:
On GSOR, the Generalized Successive Overrelaxation Method for Double Saddle-Point Problems. SIAM J. Sci. Comput. 45(5): 2185- (2023) - [j71]Juan Gao, Xinwei Liu, Yu-Hong Dai, Yakui Huang, Peng Yang:
A Family of Distributed Momentum Methods Over Directed Graphs With Linear Convergence. IEEE Trans. Autom. Control. 68(2): 1085-1092 (2023) - [j70]Weikun Chen, Ya-Feng Liu, Fan Liu, Yu-Hong Dai, Zhi-Quan Luo:
Towards Efficient Large-Scale Network Slicing: An LP Dynamic Rounding-and-Refinement Approach. IEEE Trans. Signal Process. 71: 615-630 (2023) - [c11]Zheyu Wu, Ya-Feng Liu, Bo Jiang, Yu-Hong Dai:
Efficient Quantized Constant Envelope Precoding for Multiuser Downlink Massive MIMO Systems. ICASSP 2023: 1-5 - [c10]Wei-Kun Chen, Ya-Feng Liu, Rui-Jin Zhang, Yu-Hong Dai, Zhi-Quan Luo:
An Efficient Decomposition Algorithm for Large-Scale Network Slicing. SPAWC 2023: 171-175 - [i19]Wei-Kun Chen, Ya-Feng Liu, Rui-Jin Zhang, Yu-Hong Dai, Zhi-Quan Luo:
An Efficient Decomposition Algorithm for Large-Scale Network Slicing. CoRR abs/2306.15247 (2023) - 2022
- [j69]Juan Gao, Xin-Wei Liu, Yu-Hong Dai, Yakui Huang, Peng Yang:
Achieving geometric convergence for distributed optimization with Barzilai-Borwein step sizes. Sci. China Inf. Sci. 65(4) (2022) - [j68]Yakui Huang, Yu-Hong Dai, Xin-Wei Liu, Hongchao Zhang:
On the acceleration of the Barzilai-Borwein method. Comput. Optim. Appl. 81(3): 717-740 (2022) - [j67]Liang Chen, Yu-Hong Dai, Zhou Wei:
Sufficient conditions for existence of global minimizers of functions on Hilbert spaces. J. Glob. Optim. 84(1): 137-147 (2022) - [j66]Yakui Huang, Yu-Hong Dai, Xinwei Liu, Hongchao Zhang:
On the Asymptotic Convergence and Acceleration of Gradient Methods. J. Sci. Comput. 90(1): 7 (2022) - [j65]Xin-Wei Liu, Yu-Hong Dai, Yakui Huang:
A primal-dual interior-point relaxation method with global and rapidly local convergence for nonlinear programs. Math. Methods Oper. Res. 96(3): 351-382 (2022) - [j64]Xinwei Liu, Yu-Hong Dai, Yakui Huang, Jie Sun:
A novel augmented Lagrangian method of multipliers for optimization with general inequality constraints. Math. Comput. 92(341): 1301-1330 (2022) - [c9]Wei-Kun Chen, Ya-Feng Liu, Yu-Hong Dai, Zhi-Quan Luo:
Optimal Qos-Aware Network Slicing for Service-Oriented Networks with Flexible Routing. ICASSP 2022: 5288-5292 - [c8]Zheyu Wu, Bo Jiang, Ya-Feng Liu, Yu-Hong Dai:
A Novel Negative ℓ1 Penalty Approach for Multiuser One-Bit Massive MIMO Downlink with PSK Signaling. ICASSP 2022: 5323-5327 - [i18]Na Huang, Yu-Hong Dai, Dominique Orban, Michael A. Saunders:
A semi-conjugate gradient method for solving unsymmetric positive definite linear systems. CoRR abs/2206.02951 (2022) - [i17]Na Huang, Yu-Hong Dai, Dominique Orban, Michael A. Saunders:
On GSOR, the Generalized Successive Overrelaxation Method for Double Saddle-Point Problems. CoRR abs/2208.07499 (2022) - [i16]Zheyu Wu, Ya-Feng Liu, Bo Jiang, Yu-Hong Dai:
Efficient Quantized Constant Envelope Precoding for Multiuser Downlink Massive MIMO Systems. CoRR abs/2210.14534 (2022) - [i15]Zi Xu, Ziqi Wang, Jun-Lin Wang, Yu-Hong Dai:
Zeroth-Order Alternating Gradient Descent Ascent Algorithms for a Class of Nonconvex-Nonconcave Minimax Problems. CoRR abs/2211.13668 (2022) - [i14]Huiling Zhang, Jun-Lin Wang, Zi Xu, Yu-Hong Dai:
Primal Dual Alternating Proximal Gradient Algorithms for Nonsmooth Nonconvex Minimax Problems with Coupled Linear Constraints. CoRR abs/2212.04672 (2022) - [i13]Jiang-Yao Luo, Liang Chen, Wei-Kun Chen, Jian-Hua Yuan, Yu-Hong Dai:
A Cut-and-solve Algorithm for Virtual Machine Consolidation Problem. CoRR abs/2212.12341 (2022) - 2021
- [j63]Zhi-Long Dong, Jiming Peng, Fengmin Xu, Yu-Hong Dai:
On some extended mixed integer optimization models of the Eisenberg-Noe model in systemic risk management. Int. Trans. Oper. Res. 28(6): 3014-3037 (2021) - [j62]Liang Chen, Weikun Chen, Mu-Ming Yang, Yu-Hong Dai:
An exact separation algorithm for unsplittable flow capacitated network design arc-set polyhedron. J. Glob. Optim. 81(3): 659-689 (2021) - [j61]Tengteng Yu, Xinwei Liu, Yu-Hong Dai, Jie Sun:
Stochastic Variance Reduced Gradient Methods Using a Trust-Region-Like Scheme. J. Sci. Comput. 87(1): 5 (2021) - [j60]Hui Zhang, Yu-Hong Dai, Lei Guo, Wei Peng:
Proximal-Like Incremental Aggregated Gradient Method with Linear Convergence Under Bregman Distance Growth Conditions. Math. Oper. Res. 46(1): 61-81 (2021) - [j59]Yakui Huang, Yu-Hong Dai, Xinwei Liu:
Equipping the Barzilai-Borwein Method with the Two Dimensional Quadratic Termination Property. SIAM J. Optim. 31(4): 3068-3096 (2021) - [j58]Tengteng Yu, Xinwei Liu, Yu-Hong Dai, Jie Sun:
A Minibatch Proximal Stochastic Recursive Gradient Algorithm Using a Trust-Region-Like Scheme and Barzilai-Borwein Stepsizes. IEEE Trans. Neural Networks Learn. Syst. 32(10): 4627-4638 (2021) - [j57]Weikun Chen, Ya-Feng Liu, Antonio De Domenico, Zhi-Quan Luo, Yu-Hong Dai:
Optimal Network Slicing for Service-Oriented Networks With Flexible Routing and Guaranteed E2E Latency. IEEE Trans. Netw. Serv. Manag. 18(4): 4337-4352 (2021) - [c7]Weikun Chen, Ya-Feng Liu, Yu-Hong Dai, Zhi-Quan Luo:
An Efficient Linear Programming Rounding-and-Refinement Algorithm for Large-Scale Network Slicing Problem. ICASSP 2021: 4735-4739 - [i12]Weikun Chen, Ya-Feng Liu, Yu-Hong Dai, Zhi-Quan Luo:
An efficient linear programming rounding-and-refinement algorithm for large-scale network slicing problem. CoRR abs/2102.02563 (2021) - [i11]Wei-Kun Chen, Ya-Feng Liu, Fan Liu, Yu-Hong Dai, Zhi-Quan Luo:
Towards Efficient Large-Scale Network Slicing: An LP Rounding-and-Refinement Approach. CoRR abs/2107.14404 (2021) - [i10]Wei-Kun Chen, Ya-Feng Liu, Yu-Hong Dai, Zhi-Quan Luo:
Optimal QoS-Aware Network Slicing for Service-Oriented Networks with Flexible Routing. CoRR abs/2110.03915 (2021) - [i9]Zheyu Wu, Bo Jiang, Ya-Feng Liu, Yu-Hong Dai:
A Novel Negative 𝓁1 Penalty Approach for Multiuser One-Bit Massive MIMO Downlink with PSK Signaling. CoRR abs/2110.04768 (2021) - [i8]Zheyu Wu, Bo Jiang, Ya-Feng Liu, Yu-Hong Dai:
CI-Based One-Bit Precoding for Multiuser Downlink Massive MIMO Systems with PSK Modulation: A Negative 𝓁1 Penalty Approach. CoRR abs/2110.11628 (2021) - 2020
- [j56]Zexian Liu, Hongwei Liu, Yu-Hong Dai:
An improved Dai-Kou conjugate gradient algorithm for unconstrained optimization. Comput. Optim. Appl. 75(1): 145-167 (2020) - [j55]Zhongwen Chen, Yu-Hong Dai, Jiangyan Liu:
A penalty-free method with superlinear convergence for equality constrained optimization. Comput. Optim. Appl. 76(3): 801-833 (2020) - [j54]Zhibao Li, Ka Fai Cedric Yiu, Yu-Hong Dai, Sven Nordholm:
Distributed LCMV beamformer design by randomly permuted ADMM. Digit. Signal Process. 106: 102820 (2020) - [j53]Zhi-Long Dong, Fengmin Xu, Yu-Hong Dai:
Fast algorithms for sparse portfolio selection considering industries and investment styles. J. Glob. Optim. 78(4): 763-789 (2020) - [j52]Xinwei Liu, Yu-Hong Dai:
A globally convergent primal-dual interior-point relaxation method for nonlinear programs. Math. Comput. 89(323): 1301-1329 (2020) - [j51]Yu-Hong Dai, Xin Liu, Jiawang Nie, Zaiwen Wen:
Preface. Optim. Methods Softw. 35(2): 221-222 (2020) - [j50]Yakui Huang, Yu-Hong Dai, Xinwei Liu, Hongchao Zhang:
Gradient methods exploiting spectral properties. Optim. Methods Softw. 35(4): 681-705 (2020) - [j49]Yu-Hong Dai, Florian Jarre, Felix Lieder:
On the existence of affine invariant descent directions. Optim. Methods Softw. 35(5): 938-954 (2020) - [j48]Wei Peng, Yu-Hong Dai, Hui Zhang, Lizhi Cheng:
Training GANs with centripetal acceleration. Optim. Methods Softw. 35(5): 955-973 (2020) - [i7]Weikun Chen, Ya-Feng Liu, Antonio De Domenico, Zhi-Quan Luo, Yu-Hong Dai:
Optimal Network Slicing for Service-Oriented Networks with Flexible Routing and Guaranteed E2E Latency. CoRR abs/2006.13019 (2020) - [i6]Tengteng Yu, Xinwei Liu, Yu-Hong Dai, Jie Sun:
A variable metric mini-batch proximal stochastic recursive gradient algorithm with diagonal Barzilai-Borwein stepsize. CoRR abs/2010.00817 (2020)
2010 – 2019
- 2019
- [j47]Yu-Hong Dai, Yakui Huang, Xinwei Liu:
A family of spectral gradient methods for optimization. Comput. Optim. Appl. 74(1): 43-65 (2019) - [j46]Zhibao Li, Yu-Hong Dai, Huan Gao:
Alternating projection method for a class of tensor equations. J. Comput. Appl. Math. 346: 490-504 (2019) - [j45]Na Huang, Yu-Hong Dai, QiYa Hu:
Uzawa methods for a class of block three-by-three saddle-point problems. Numer. Linear Algebra Appl. 26(6) (2019) - 2018
- [j44]Fengmin Xu, Meihua Wang, Yu-Hong Dai, Dachuan Xu:
A sparse enhanced indexation model with chance and cardinality constraints. J. Glob. Optim. 70(1): 5-25 (2018) - [j43]Weikun Chen, Liang Chen, Mu-Ming Yang, Yu-Hong Dai:
Generalized coefficient strengthening cuts for mixed integer programming. J. Glob. Optim. 70(1): 289-306 (2018) - [j42]Wanyou Cheng, Yu-Hong Dai:
Gradient-based method with active set strategy for ℓ1 optimization. Math. Comput. 87(311): 1283-1305 (2018) - 2017
- [j41]Rui Diao, Ya-Feng Liu, Yu-Hong Dai:
A new fully polynomial time approximation scheme for the interval subset sum problem. J. Glob. Optim. 68(4): 749-775 (2017) - [i5]Rui Diao, Ya-Feng Liu, Yu-Hong Dai:
A New Fully Polynomial Time Approximation Scheme for the Interval Subset Sum Problem. CoRR abs/1704.06928 (2017) - 2016
- [j40]Zhongwen Chen, Yu-Hong Dai:
A line search exact penalty method with bi-object strategy for nonlinear constrained optimization. J. Comput. Appl. Math. 300: 245-258 (2016) - [j39]Ya-Feng Liu, Shiqian Ma, Yu-Hong Dai, Shuzhong Zhang:
A smoothing SQP framework for a class of composite Lq minimization over polyhedron. Math. Program. 158(1-2): 467-500 (2016) - [c6]Conghui Tan, Shiqian Ma, Yu-Hong Dai, Yuqiu Qian:
Barzilai-Borwein Step Size for Stochastic Gradient Descent. NIPS 2016: 685-693 - [i4]Conghui Tan, Shiqian Ma, Yu-Hong Dai, Yuqiu Qian:
Barzilai-Borwein Step Size for Stochastic Gradient Descent. CoRR abs/1605.04131 (2016) - 2015
- [j38]Cai-Xia Kou, Yu-Hong Dai:
A Modified Self-Scaling Memoryless Broyden-Fletcher-Goldfarb-Shanno Method for Unconstrained Optimization. J. Optim. Theory Appl. 165(1): 209-224 (2015) - [j37]Bo Jiang, Yu-Hong Dai:
A framework of constraint preserving update schemes for optimization on Stiefel manifold. Math. Program. 153(2): 535-575 (2015) - [j36]Chun-Lin Hao, Chun-Feng Cui, Yu-Hong Dai:
A sequential subspace projection method for extreme Z-eigenvalues of supersymmetric tensors. Numer. Linear Algebra Appl. 22(2): 283-298 (2015) - [j35]Ya-Feng Liu, Yu-Hong Dai, Shiqian Ma:
Joint Power and Admission Control: Non-Convex Lq Approximation and An Effective Polynomial Time Deflation Approach. IEEE Trans. Signal Process. 63(14): 3641-3656 (2015) - 2014
- [j34]Yi-Qing Hu, Chun-Lin Hao, Yu-Hong Dai:
Projected gradient algorithms for optimization over order simplices. Optim. Methods Softw. 29(5): 1090-1117 (2014) - [j33]Chun-Feng Cui, Yu-Hong Dai, Jiawang Nie:
All Real Eigenvalues of Symmetric Tensors. SIAM J. Matrix Anal. Appl. 35(4): 1582-1601 (2014) - [j32]Ya-Feng Liu, Yu-Hong Dai:
On the Complexity of Joint Subcarrier and Power Allocation for Multi-User OFDMA Systems. IEEE Trans. Signal Process. 62(3): 583-596 (2014) - 2013
- [j31]Yu-Hong Dai:
A perfect example for the BFGS method. Math. Program. 138(1-2): 501-530 (2013) - [j30]Bo Jiang, Yu-Hong Dai:
Feasible Barzilai-Borwein-like methods for extreme symmetric eigenvalue problems. Optim. Methods Softw. 28(4): 756-784 (2013) - [j29]Yu-Hong Dai, Cai-Xia Kou:
A Nonlinear Conjugate Gradient Algorithm with an Optimal Property and an Improved Wolfe Line Search. SIAM J. Optim. 23(1): 296-320 (2013) - [j28]Ya-Feng Liu, Mingyi Hong, Yu-Hong Dai:
Max-Min Fairness Linear Transceiver Design Problem for a Multi-User SIMO Interference Channel is Polynomial Time Solvable. IEEE Signal Process. Lett. 20(1): 27-30 (2013) - [j27]Ya-Feng Liu, Yu-Hong Dai, Zhi-Quan Luo:
Joint Power and Admission Control via Linear Programming Deflation. IEEE Trans. Signal Process. 61(6): 1327-1338 (2013) - [j26]Ya-Feng Liu, Yu-Hong Dai, Zhi-Quan Luo:
Max-Min Fairness Linear Transceiver Design for a Multi-User MIMO Interference Channel. IEEE Trans. Signal Process. 61(9): 2413-2423 (2013) - [c5]Ya-Feng Liu, Yu-Hong Dai:
Joint power and admission control via p norm minimization deflation. ICASSP 2013: 4789-4793 - [i3]Ya-Feng Liu, Yu-Hong Dai:
Joint power and admission control via p norm minimization deflation. CoRR abs/1303.1633 (2013) - [i2]Ya-Feng Liu, Yu-Hong Dai, Shiqian Ma:
Joint Power and Admission Control: Non-Convex Approximation and An Efficient Polynomial Time Deflation Approach. CoRR abs/1311.3045 (2013) - 2012
- [j25]Zi Xu, Yu-Hong Dai:
New stochastic approximation algorithms with adaptive step sizes. Optim. Lett. 6(8): 1831-1846 (2012) - [c4]Ya-Feng Liu, Yu-Hong Dai, Zhi-Quan Luo:
Joint power and admission control via linear programming deflation. ICASSP 2012: 2873-2876 - [i1]Ya-Feng Liu, Yu-Hong Dai:
On the Complexity of Joint Subcarrier and Power Allocation for Multi-User OFDMA Systems. CoRR abs/1212.5024 (2012) - 2011
- [j24]Yu-Hong Dai:
Convergence of conjugate gradient methods with constant stepsizes. Optim. Methods Softw. 26(6): 895-909 (2011) - [j23]Ya-Feng Liu, Yu-Hong Dai, Zhi-Quan Luo:
Coordinated Beamforming for MISO Interference Channel: Complexity Analysis and Efficient Algorithms. IEEE Trans. Signal Process. 59(3): 1142-1157 (2011) - [c3]Ya-Feng Liu, Yu-Hong Dai, Zhi-Quan Luo:
Max-Min Fairness Linear Transceiver Design for a Multi-User MIMO Interference Channel. ICC 2011: 1-5 - 2010
- [j22]Yun-Shan Fu, Yu-Hong Dai:
Improved Projected Gradient Algorithms for Singly Linearly Constrained Quadratic Programs Subject to Lower and Upper Bounds. Asia Pac. J. Oper. Res. 27(1): 71-84 (2010) - [c2]Ya-Feng Liu, Yu-Hong Dai, Zhi-Quan Luo:
On the complexity of optimal coordinated downlink beamforming. ICASSP 2010: 3274-3277
2000 – 2009
- 2009
- [j21]Gaohang Yu, Liqun Qi, Yu-Hong Dai:
On Nonmonotone Chambolle Gradient Projection Algorithms for Total Variation Image Restoration. J. Math. Imaging Vis. 35(2): 143-154 (2009) - [c1]Fuxin Li, Yun-Shan Fu, Yu-Hong Dai, Cristian Sminchisescu, Jue Wang:
Kernel Learning by Unconstrained Optimization. AISTATS 2009: 328-335 - 2008
- [j20]Liping Wang, Yu-Hong Dai:
Left conjugate gradient method for non-Hermitian linear systems. Numer. Linear Algebra Appl. 15(10): 891-909 (2008) - 2007
- [j19]Yi-Qing Hu, Yu-Hong Dai:
Inexact Barzilai-Borwein method for saddle point problems. Numer. Linear Algebra Appl. 14(4): 299-317 (2007) - 2006
- [j18]Y. H. Dai, X. Q. Yang:
A New Gradient Method with an Optimal Stepsize Property. Comput. Optim. Appl. 33(1): 73-88 (2006) - [j17]Bin Zhou, Li Gao, Yu-Hong Dai:
Gradient Methods with Adaptive Step-Sizes. Comput. Optim. Appl. 35(1): 69-86 (2006) - [j16]Yu-Hong Dai, Roger Fletcher:
New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds. Math. Program. 106(3): 403-421 (2006) - [j15]Yu-Hong Dai:
Fast Algorithms for Projection on an Ellipsoid. SIAM J. Optim. 16(4): 986-1006 (2006) - 2005
- [j14]Yu-Hong Dai, Roger Fletcher:
On the asymptotic behaviour of some new gradient methods. Math. Program. 103(3): 541-559 (2005) - [j13]Yu-Hong Dai, Roger Fletcher:
Projected Barzilai-Borwein methods for large-scale box-constrained quadratic programming. Numerische Mathematik 100(1): 21-47 (2005) - 2004
- [j12]Yu-Hong Dai, Li-Zhi Liao, Duan Li:
On Restart Procedures for the Conjugate Gradient Method. Numer. Algorithms 35(2-4): 249-260 (2004) - 2003
- [j11]Yu-Hong Dai:
A family of hybrid conjugate gradient methods for unconstrained optimization. Math. Comput. 72(243): 1317-1328 (2003) - [j10]Yu-Hong Dai, José Mario Martínez, Jin Yun Yuan:
An increasing-angle property of the conjugate gradient method and the implementation of large-scale minimization algorithms with line searches. Numer. Linear Algebra Appl. 10(4): 323-334 (2003) - 2002
- [j9]Yu-Hong Dai, Jin Yun Yuan, Ya-Xiang Yuan:
Modified Two-Point Stepsize Gradient Methods for Unconstrained Optimization. Comput. Optim. Appl. 22(1): 103-109 (2002) - [j8]Yu-Hong Dai:
Convergence Properties of the BFGS Algoritm. SIAM J. Optim. 13(3): 693-701 (2002) - 2001
- [j7]Y. H. Dai, Ya-Xiang Yuan:
An Efficient Hybrid Conjugate Gradient Method for Unconstrained Optimization. Ann. Oper. Res. 103(1-4): 33-47 (2001) - [j6]Yu-Hong Dai, Ya-Xiang Yuan:
A three-parameter family of nonlinear conjugate gradient methods. Math. Comput. 70(235): 1155-1167 (2001) - [j5]Yu-Hong Dai, Hongchao Zhang:
Adaptive Two-Point Stepsize Gradient Algorithm. Numer. Algorithms 27(4): 377-385 (2001) - [j4]Yu-Hong Dai:
New properties of a nonlinear conjugate gradient method. Numerische Mathematik 89(1): 83-98 (2001) - 2000
- [j3]Yu-Hong Dai, Jiye Han, Guanghui Liu, Defeng Sun, Hongxia Yin, Ya-Xiang Yuan:
Convergence Properties of Nonlinear Conjugate Gradient Methods. SIAM J. Optim. 10(2): 345-358 (2000)
1990 – 1999
- 1999
- [j2]Yu-Hong Dai, Ya-Xiang Yuan:
Global convergence of the method of shortest residuals. Numerische Mathematik 83(4): 581-598 (1999) - [j1]Y. H. Dai, Ya-Xiang Yuan:
A Nonlinear Conjugate Gradient Method with a Strong Global Convergence Property. SIAM J. Optim. 10(1): 177-182 (1999)
Coauthor Index
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