Evolving artificial neural network ensembles
暂无分享,去创建一个
[1] Catherine Blake,et al. UCI Repository of machine learning databases , 1998 .
[2] C. Cowan,et al. Adaptive Filters and Equalisers , 1988 .
[3] David W. Opitz,et al. Generating Accurate and Diverse Members of a Neural-Network Ensemble , 1995, NIPS.
[4] Lars Kai Hansen,et al. Neural Network Ensembles , 1990, IEEE Trans. Pattern Anal. Mach. Intell..
[5] Xin Yao,et al. Every Niching Method has its Niche: Fitness Sharing and Implicit Sharing Compared , 1996, PPSN.
[6] Xin Yao,et al. Evolving artificial neural networks , 1999, Proc. IEEE.
[7] Lutz Prechelt,et al. PROBEN 1 - a set of benchmarks and benchmarking rules for neural network training algorithms , 1994 .
[8] Xin Yao,et al. An analysis of diversity measures , 2006, Machine Learning.
[9] David B. Fogel,et al. CONTINUOUS EVOLUTIONARY PROGRAMMING: ANALYSIS AND EXPERIMENTS , 1995 .
[10] Xin Yao,et al. The Evolution of Connectionist Networks , 1994 .
[11] H. Abbass. The self-adaptive Pareto differential evolution algorithm , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
[12] Terry Dartnall,et al. Artificial Intelligence and Creativity , 1994 .
[13] Lutz Prechelt,et al. Some notes on neural learning algorithm benchmarking , 1995, Neurocomputing.
[14] Yoonseon Song,et al. Evolutionary programming using the Levy probability distribution , 1999 .
[15] Dušan Petrovački,et al. Evolutional development of a multilevel neural network , 1993, Neural Networks.
[16] Sherif Hashem,et al. Optimal Linear Combinations of Neural Networks , 1997, Neural Networks.
[17] Ferdinand Hergert,et al. Improving model selection by nonconvergent methods , 1993, Neural Networks.
[18] Xin Yao,et al. An empirical study of genetic operators in genetic algorithms , 1993, Microprocess. Microprogramming.
[19] Hussein A. Abbass. Pareto Neuro-Ensembles , 2003, Australian Conference on Artificial Intelligence.
[20] Peter J. Angeline,et al. An evolutionary algorithm that constructs recurrent neural networks , 1994, IEEE Trans. Neural Networks.
[21] Xin Yao,et al. Ensemble structure of evolutionary artificial neural networks , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.
[22] Herbert F. Jelinek,et al. Complex systems : from local interactions to global phenomena , 1996 .
[23] R. K. Ursem. Multi-objective Optimization using Evolutionary Algorithms , 2009 .
[24] Xin Yao,et al. Evolutionary Artificial Neural Networks , 1993, Int. J. Neural Syst..
[25] J. Rissanen,et al. Modeling By Shortest Data Description* , 1978, Autom..
[26] Kurt Hornik,et al. Learning in linear neural networks: a survey , 1995, IEEE Trans. Neural Networks.
[27] Xin Yao,et al. A Preliminary Study on Designing Artiicial Neural Networks Using Co-evolution , 1995 .
[28] Xin Yao,et al. Evolutionary ensembles with negative correlation learning , 2000, IEEE Trans. Evol. Comput..
[29] Xin Yao,et al. Making use of population information in evolutionary artificial neural networks , 1998, IEEE Trans. Syst. Man Cybern. Part B.
[30] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[31] Xin Yao,et al. Ensemble Learning Using Multi-Objective Evolutionary Algorithms , 2006, J. Math. Model. Algorithms.
[32] M. Perrone. Improving regression estimation: Averaging methods for variance reduction with extensions to general convex measure optimization , 1993 .
[33] James T. Kwok,et al. Constructive algorithms for structure learning in feedforward neural networks for regression problems , 1997, IEEE Trans. Neural Networks.
[34] Shun-ichi Amari,et al. Mutual information of sparsely coded associative memory with self-control and ternary neurons , 2000, Neural Networks.
[35] Anders Krogh,et al. Neural Network Ensembles, Cross Validation, and Active Learning , 1994, NIPS.
[36] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[37] D. Opitz,et al. Popular Ensemble Methods: An Empirical Study , 1999, J. Artif. Intell. Res..
[38] Lawrence J. Fogel,et al. Artificial Intelligence through Simulated Evolution , 1966 .
[39] Amanda J. C. Sharkey,et al. On Combining Artificial Neural Nets , 1996, Connect. Sci..
[40] Hussein A. Abbass,et al. Speeding Up Backpropagation Using Multiobjective Evolutionary Algorithms , 2003, Neural Computation.
[41] Peter J. B. Hancock,et al. Genetic algorithms and permutation problems: a comparison of recombination operators for neural net structure specification , 1992, [Proceedings] COGANN-92: International Workshop on Combinations of Genetic Algorithms and Neural Networks.
[42] Gavin Brown,et al. Negative Correlation Learning and the Ambiguity Family of Ensemble Methods , 2003, Multiple Classifier Systems.
[43] Xin Yao,et al. Speciation as automatic categorical modularization , 1997, IEEE Trans. Evol. Comput..
[44] Xin Yao,et al. A new evolutionary system for evolving artificial neural networks , 1997, IEEE Trans. Neural Networks.
[45] Xin Yao,et al. A constructive algorithm for training cooperative neural network ensembles , 2003, IEEE Trans. Neural Networks.
[46] J. MacQueen. Some methods for classification and analysis of multivariate observations , 1967 .
[47] Rainer Storn,et al. Minimizing the real functions of the ICEC'96 contest by differential evolution , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.
[48] James T. Kwok,et al. Objective functions for training new hidden units in constructive neural networks , 1997, IEEE Trans. Neural Networks.
[49] Richard K. Belew,et al. Evolving networks: using the genetic algorithm with connectionist learning , 1990 .
[50] Xin Yao,et al. Multi-network evolutionary systems and automatic decomposition of complex problems , 2006, Int. J. Gen. Syst..
[51] Xin Yao,et al. Ensemble learning via negative correlation , 1999, Neural Networks.
[52] Xin Yao,et al. A review of evolutionary artificial neural networks , 1993, Int. J. Intell. Syst..
[53] J. D. Schaffer,et al. Combinations of genetic algorithms and neural networks: a survey of the state of the art , 1992, [Proceedings] COGANN-92: International Workshop on Combinations of Genetic Algorithms and Neural Networks.
[54] Xin Yao,et al. Diversity creation methods: a survey and categorisation , 2004, Inf. Fusion.
[55] Thomas G. Dietterich. Machine-Learning Research Four Current Directions , 1997 .
[56] Thomas Bäck,et al. Evolutionary computation: Toward a new philosophy of machine intelligence , 1997, Complex..
[57] X. Yao,et al. How to Make Best Use of Evolutionary Learning , 1996 .
[58] Samir W. Mahfoud. Niching methods for genetic algorithms , 1996 .
[59] H. Abbass,et al. PDE: a Pareto-frontier differential evolution approach for multi-objective optimization problems , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).
[60] A. Krogh,et al. Statistical mechanics of ensemble learning , 1997 .
[61] Hussein A. Abbass,et al. Pareto neuro-evolution: constructing ensemble of neural networks using multi-objective optimization , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..
[62] Kalyanmoy Deb,et al. MULTI-OBJECTIVE FUNCTION OPTIMIZATION USING NON-DOMINATED SORTING GENETIC ALGORITHMS , 1994 .
[63] Xin Yao,et al. Evolutionary programming made faster , 1999, IEEE Trans. Evol. Comput..