Operations Research Transactions ›› 2021, Vol. 25 ›› Issue (2): 81-92.doi: 10.15960/j.cnki.issn.1007-6093.2021.02.006
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Xiaohui QIAN1, Xiangmei WANG1,*()
Received:
2019-12-30
Online:
2021-06-15
Published:
2021-05-06
Contact:
Xiangmei WANG
E-mail:xmwang2@gzu.edu.cn
CLC Number:
Xiaohui QIAN, Xiangmei WANG. A scaled incremental gradient method[J]. Operations Research Transactions, 2021, 25(2): 81-92.
"
算法 | xk | 迭代次数k | 运行时间t/s |
初始点x0=(50, 50), 精度ε=0.3 | |||
IGA[ | (54.525 5, 51.111 2) | 476 813 | 109.72 |
SIGA | (54.526 9, 51.115 8) | 59 | 0.10 |
初始点x0=(60, 60), 精度ε=0.185 | |||
IGA[ | (61.383 7, 58.300 0) | 57 280 | 13.10 |
SIGA | (61.253 2, 58.022 0) | 5 | 0.01 |
初始点x0=(80, 80), 精度ε=0.5 | |||
IGA[ | (75.710 9, 73.123 5) | 233 133 | 54.12 |
SIGA | (75.566 1, 73.220 3) | 11 | 0.02 |
1 |
Bertsekas D P . Incremental least squares methods and the extended kalman filter[J]. SIAM Journal on Optimization, 1996, 6 (3): 807- 822.
doi: 10.1137/S1052623494268522 |
2 |
Bertsekas D P . A new class of incremental gradient methods for least squares problems[J]. SIAM Journal on Optimization, 1997, 7 (4): 913- 926.
doi: 10.1137/S1052623495287022 |
3 |
Moriyama H , Yamashita N , Fukushima M . The incremental Gauss-Newton algorithm with adaptive stepsize rule[J]. Computational Optimization and Applications, 2003, 26 (2): 107- 141.
doi: 10.1023/A:1025703629626 |
4 |
Gurbuzbalaban M , Ozdaglar A , Parrilo P . A globally convergent incremental newton method[J]. Mathematical Programming, 2015, 151 (1): 283- 313.
doi: 10.1007/s10107-015-0897-y |
5 |
Blatt D , Hero A , Gauchman H . A convergent incremental gradient method with a constant stepsize[J]. SIAM Journal on Optimization, 2007, 18 (1): 29- 51.
doi: 10.1137/040615961 |
6 |
Bottou L , Le Cun Y . On-line learning for very large data sets[J]. Applied Stochastic Models in Business and Industry, 2005, 21 (2): 137- 151.
doi: 10.1002/asmb.538 |
7 | Roux N L, Schmidt M, Bach F R. A stochastic gradient method with an exponential convergence rate for finite training sets [C]//ICONIP 2018 2018: 25th International Conference on Neural Information Processing Systems, 2018. |
8 |
Grippo L . A class of unconstrained minimization methods for neural network training[J]. Optimization Methods and Software, 1994, 4 (2): 135- 150.
doi: 10.1080/10556789408805583 |
9 |
Mangasarian O L , Solodov M V . Serial and parallel backpropagation convergence via nonmonotone perturbed minimization[J]. Optimization Methods and Software, 1994, 4 (2): 103- 116.
doi: 10.1080/10556789408805581 |
10 |
Bertsekas D P , Tsitsiklis J N . Gradient convergence in gradient methods with errors[J]. SIAM Journal on Optimization, 2000, 10 (3): 627- 642.
doi: 10.1137/S1052623497331063 |
11 | BertsekasD P. 非线性规划[M]. 第2版 北京: 清华大学出版社, 2013. |
12 | 王宜举, 修乃华. 非线性最优化理论与方法[M]. 北京: 科学出版社, 2015. |
13 | 袁亚湘, 孙文瑜. 最优化理论与方法[M]. 北京: 科学出版社, 2007. |
14 | 陈宝林. 最优化理论与算法[M]. 北京: 清华大学出版社, 2005. |
15 | 马昌凤, 柯艺芬, 谢亚君. 最优化计算方法及其MATLAB程序实现[M]. 北京: 国防教育出版社, 2017. |
16 | Trefethen . Spectral Methods in MATLAB[M]. New York: SIAM, 2000. |
17 | Rabbat M G, Nowak R D. Decentralized source localization and tracking[C]//2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, New York: IEEE, 2004. |
18 | Sheng X , Hu Y H . Information Processing in Sensor Networks[M]. California: Springer, 2003. |
19 |
Chen J C , Yao K , Hudson R E . Source localization and beamforming[J]. IEEE Signal Processing Magazine, 2002, 19, 30- 39.
doi: 10.1109/79.985676 |
20 | Huber P . Robust Statistics[M]. New York: John Wiley and Sons, 1981. |
21 | Polyak B T . Introduction to Optimization[M]. New York: Chapman & Hall, 1987. |
22 | Rey W J J . Introduction to Robust and Quasi-Robust Statistical Methods[M]. Berlin: SpringerVerlag, 1983. |
23 | Shor N Z . Minimization Methods for Non-differentiable Functions[M]. Kiev: Naukova Dumka, 1979. |
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