Robust combining methods in committee neural networks
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[1] Sargur N. Srihari,et al. Decision Combination in Multiple Classifier Systems , 1994, IEEE Trans. Pattern Anal. Mach. Intell..
[2] David W. Opitz,et al. Actively Searching for an E(cid:11)ective Neural-Network Ensemble , 1996 .
[3] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.
[4] James C. Bezdek,et al. Decision templates for multiple classifier fusion: an experimental comparison , 2001, Pattern Recognit..
[5] David H. Wolpert,et al. Stacked generalization , 1992, Neural Networks.
[6] Andrew W. Moore,et al. Gradient Descent for General Reinforcement Learning , 1998, NIPS.
[7] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.
[8] Adam Krzyżak,et al. Methods of combining multiple classifiers and their applications to handwriting recognition , 1992, IEEE Trans. Syst. Man Cybern..
[9] Moumen T. El-Melegy,et al. Robust Training of Artificial Feedforward Neural Networks , 2009, Foundations of Computational Intelligence.
[10] Carlos Soares,et al. A Comparison of Ranking Methods for Classification Algorithm Selection , 2000, ECML.
[11] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[12] Martin A. Riedmiller,et al. A direct adaptive method for faster backpropagation learning: the RPROP algorithm , 1993, IEEE International Conference on Neural Networks.
[13] D. Opitz,et al. Popular Ensemble Methods: An Empirical Study , 1999, J. Artif. Intell. Res..
[14] Josef Skrzypek,et al. Synergy of Clustering Multiple Back Propagation Networks , 1989, NIPS.
[15] Harris Drucker,et al. Boosting and Other Ensemble Methods , 1994, Neural Computation.
[16] David W. Opitz,et al. An Empirical Evaluation of Bagging and Boosting , 1997, AAAI/IAAI.
[17] D. Marquardt. An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .
[18] Lars Kai Hansen,et al. Neural Network Ensembles , 1990, IEEE Trans. Pattern Anal. Mach. Intell..
[19] Robert A. Jacobs,et al. Methods For Combining Experts' Probability Assessments , 1995, Neural Computation.
[20] Maria Petrou,et al. Use of Dempster-Shafer theory to combine classifiers which use different class boundaries , 2003, Pattern Analysis & Applications.
[21] Sung-Bae Cho,et al. An HMM/MLP Architecture for Sequence Recognition , 1995, Neural Computation.
[22] Anders Krogh,et al. Neural Network Ensembles, Cross Validation, and Active Learning , 1994, NIPS.
[23] M. Hill,et al. Data analysis in community and landscape ecology , 1987 .
[24] David J. C. MacKay,et al. Bayesian Interpolation , 1992, Neural Computation.
[25] F. Klawonn,et al. Fuzzy Cluster Analysis from the Viewpoint of Robust Statistics , 2009 .
[26] Antony Browne,et al. Neural network ensembles: combining multiple models for enhanced performance using a multistage approach , 2004, Expert Syst. J. Knowl. Eng..
[27] Ludmila I. Kuncheva,et al. Classifier Ensembles for Changing Environments , 2004, Multiple Classifier Systems.
[28] Robert E. Schapire,et al. The strength of weak learnability , 1990, Mach. Learn..
[29] Peter J. Huber,et al. Wiley Series in Probability and Statistics , 2011 .
[30] Kenneth Levenberg. A METHOD FOR THE SOLUTION OF CERTAIN NON – LINEAR PROBLEMS IN LEAST SQUARES , 1944 .
[31] Bruce W. Schmeiser,et al. Optimal linear combinations of neural networks: an overview , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).
[32] Martin Fodslette Meiller. A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning , 1993 .