Recent Results on No-Free-Lunch Theorems for Optimization
暂无分享,去创建一个
[1] D. Wolpert,et al. No Free Lunch Theorems for Search , 1995 .
[2] T. M. English. Optimization is easy and learning is hard in the typical function , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).
[3] David H. Wolpert,et al. Remarks on a recent paper on the "no free lunch" theorems , 2001, IEEE Trans. Evol. Comput..
[4] David H. Wolpert,et al. No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..
[5] Christian Igel,et al. Graph isomorphisms effect on structure optimization of neural networks , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).
[6] Marc Toussaint,et al. Neutrality and self-adaptation , 2003, Natural Computing.
[7] D. WhitleyComputer. A Free Lunch Proof for Gray versus Binary Encodings , 1999 .
[8] Thomas Jansen,et al. Optimization with randomized search heuristics - the (A)NFL theorem, realistic scenarios, and difficult functions , 2002, Theor. Comput. Sci..
[9] Marc Toussaint,et al. On Classes of Functions for which No Free Lunch Results Hold , 2001, Inf. Process. Lett..
[10] Patrick D. Surry,et al. Fundamental Limitations on Search Algorithms: Evolutionary Computing in Perspective , 1995, Computer Science Today.