Learning in the feed-forward random neural network: A critical review
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[1] Jooyoung Park,et al. Universal Approximation Using Radial-Basis-Function Networks , 1991, Neural Computation.
[2] Jesús Cid-Sueiro,et al. Cost functions to estimate a posteriori probabilities in multiclass problems , 1999, IEEE Trans. Neural Networks.
[3] Zwe-Lee Gaing,et al. Particle swarm optimization to solving the economic dispatch considering the generator constraints , 2003 .
[4] Don R. Hush,et al. Error surfaces for multilayer perceptrons , 1992, IEEE Trans. Syst. Man Cybern..
[5] Yue Shi,et al. A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).
[6] Klaus-Robert Müller,et al. Efficient BackProp , 2012, Neural Networks: Tricks of the Trade.
[7] Said E. El-Khamy,et al. Random neural network filter for land mine detection , 1999, Proceedings of the Sixteenth National Radio Science Conference. NRSC'99 (IEEE Cat. No.99EX249).
[8] Terence Soule,et al. Comparison of Genetic Algorithm and Particle Swarm Optimizer When Evolving a Recurrent Neural Network , 2003, GECCO.
[9] William H. Press,et al. Numerical recipes in C , 2002 .
[10] John C. Platt,et al. Fast training of support vector machines using sequential minimal optimization, advances in kernel methods , 1999 .
[11] Andreas Stafylopatis,et al. Training the random neural network using quasi-Newton methods , 2000, Eur. J. Oper. Res..
[12] Erol Gelenbe,et al. Wafer surface reconstruction from top–down scanning electron microscope images , 2004 .
[13] Pierre Tirilly,et al. Evaluating Users' Satisfaction in Packet Networks Using Random Neural Networks , 2006, ICANN.
[14] F. Aluffi-Pentini,et al. Global optimization and stochastic differential equations , 1985 .
[15] Erol Gelenbe,et al. Random network learning and image compression , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).
[16] Gerardo Rubino,et al. Controlling Multimedia QoS in the Future Home Network Using the PSQA Metric , 2006, Comput. J..
[17] Erol Gelenbe,et al. Neural network methods for volumetric magnetic resonance imaging of the human brain , 1996 .
[18] Shangxu Hu,et al. A New Approach to Improve Particle Swarm Optimization , 2003, GECCO.
[19] José Aguilar,et al. Resolution of pattern recognition problems using a hybrid Genetic/Random Neural Network learning algorithm , 2005, Pattern Analysis and Applications.
[20] Michael Georgiopoulos,et al. Properties of learning related to pattern diversity in ART1 , 1991, Neural Networks.
[21] Erol Gelenbe,et al. Feature-based RNN target recognition , 1998, Defense, Security, and Sensing.
[22] X. Xu,et al. A case study of solving optimization problems using neural networks , 1988, Neural Networks.
[23] Geoffrey E. Hinton,et al. Learning internal representations by error propagation , 1986 .
[24] Georgia Sakellari,et al. The Cognitive Packet Network: A Survey , 2010, Comput. J..
[25] Michael Georgiopoulos,et al. Convergence Properties of Learning in ART1 , 1990, Neural Computation.
[26] M. A. Abido. Optimal des'ign of Power System Stabilizers Using Particle Swarm Opt'imization , 2002, IEEE Power Engineering Review.
[27] Catherine Blake,et al. UCI Repository of machine learning databases , 1998 .
[28] Ugur Halici,et al. Reinforcement learning with internal expectation for the random neural network , 2000, Eur. J. Oper. Res..
[29] Erol Gelenbe,et al. Detecting Denial of Service Attacks with Bayesian Classifiers and the Random Neural Network , 2007, 2007 IEEE International Fuzzy Systems Conference.
[30] Michael Georgiopoulos,et al. Properties of learning in ARTMAP , 1994, Neural Networks.
[31] Erol Gelenbe,et al. Video quality and traffic QoS in learning-based subsampled and receiver-interpolated video sequences , 2000, IEEE Journal on Selected Areas in Communications.
[32] Heinz Mühlenbein,et al. Predictive Models for the Breeder Genetic Algorithm I. Continuous Parameter Optimization , 1993, Evolutionary Computation.
[33] Cheng-Yan Kao,et al. A Robust Evolutionary Algorithm for Training Neural Networks , 2001, Neural Computing & Applications.
[34] N. B. Karayiannis. ALADIN: algorithms for Learning and Architecture DetermINation , 1994 .
[35] Zhi-Hong Mao,et al. Function approximation with spiked random networks , 1999, IEEE Trans. Neural Networks.
[36] M. A. Abido,et al. Optimal power flow using particle swarm optimization , 2002 .
[37] V. Nedeljkovic,et al. A novel multilayer neural networks training algorithm that minimizes the probability of classification error , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol.II. Conference B: Pattern Recognition Methodology and Systems.
[38] Huihe Shao,et al. An ANN's evolved by a new evolutionary system and its application , 2000, Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187).
[39] Teresa Bernarda Ludermir,et al. Particle Swarm Optimization of Neural Network Architectures andWeights , 2007, 7th International Conference on Hybrid Intelligent Systems (HIS 2007).
[40] Stephen Grossberg,et al. Adaptive pattern classification and universal recoding: II. Feedback, expectation, olfaction, illusions , 1976, Biological Cybernetics.
[41] Gulay Oke,et al. Likelihood ratios and recurrent random neural networks in detection of denial of service attacks , 2007 .
[42] Etienne Barnard,et al. Avoiding false local minima by proper initialization of connections , 1992, IEEE Trans. Neural Networks.
[43] Yan-Da Li,et al. Approximation by random networks with bounded number of layers , 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).
[44] D. E. Goldberg,et al. Genetic Algorithms in Search , 1989 .
[45] James L. McClelland,et al. Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations , 1986 .
[46] Heekuck Oh,et al. Neural Networks for Pattern Recognition , 1993, Adv. Comput..
[47] S. Katagiri,et al. Discriminative Learning for Minimum Error Classification , 2009 .
[48] S. García,et al. An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for all Pairwise Comparisons , 2008 .
[49] Ge Xiurun,et al. An improved PSO-based ANN with simulated annealing technique , 2005, Neurocomputing.
[50] Taskin Koçak,et al. Survey of random neural network applications , 2000, Eur. J. Oper. Res..
[51] Erol Gelenbe,et al. Low bit-rate video compression with neural networks and temporal subsampling , 1996, Proc. IEEE.
[52] Erol Gelenbe,et al. Video compression with random neural networks , 1996, Proceedings of International Workshop on Neural Networks for Identification, Control, Robotics and Signal/Image Processing.
[53] D. R. Hush,et al. Error surfaces for multi-layer perceptrons , 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.
[54] Gerardo Rubino,et al. Real-Time Video Quality Assessment in Packet Networks: A Neural Network Model , 2001 .
[55] Erol Gelenbe,et al. Learning in the Recurrent Random Neural Network , 1992, Neural Computation.
[56] Georgios Loukas,et al. A Denial of Service Detector based on Maximum Likelihood Detection and the Random Neural Network , 2007, Comput. J..
[57] Erol Gelenbe,et al. Autonomous smart routing for network QoS , 2004 .
[58] G. J. Gibson,et al. On the decision regions of multilayer perceptrons , 1990, Proc. IEEE.
[59] E. Cantu-Paz,et al. An empirical comparison of combinations of evolutionary algorithms and neural networks for classification problems , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[60] Brian D. Ripley,et al. Neural Networks and Related Methods for Classification , 1994 .
[61] James Kennedy,et al. Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.
[62] Gerardo Rubino,et al. Levenberg - Marquardt Training Algorithms for Random Neural Networks , 2011, Comput. J..
[63] Erol Gelenbe,et al. Image and video compression , 1998 .
[64] J. Salerno,et al. Using the particle swarm optimization technique to train a recurrent neural model , 1997, Proceedings Ninth IEEE International Conference on Tools with Artificial Intelligence.
[65] Yaochu Jin,et al. Pareto-based Multi-Objective Machine Learning , 2007, 7th International Conference on Hybrid Intelligent Systems (HIS 2007).
[66] Erol Gelenbe,et al. Image Enhacement and Fusion with the Random Neural Network , 1997, Turkish Journal of Electrical Engineering and Computer Sciences.
[67] Wei-Yin Loh,et al. A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-Three Old and New Classification Algorithms , 2000, Machine Learning.
[68] Stephen Grossberg,et al. The ART of adaptive pattern recognition by a self-organizing neural network , 1988, Computer.
[69] Georgios C. Anagnostopoulos,et al. Exemplar-based pattern recognition via semi-supervised learning , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..
[70] R. Raghavan,et al. Gradient descent fails to separate , 1988, IEEE 1988 International Conference on Neural Networks.
[71] Bernhard Sendhoff,et al. Evolutionary Multi-objective Optimization of Spiking Neural Networks , 2007, ICANN.
[72] J. Dennis,et al. A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multicriteria optimization problems , 1997 .
[73] Janez Demsar,et al. Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..
[74] Georgios C. Anagnostopoulos,et al. Category regions as new geometrical concepts in Fuzzy-ART and Fuzzy-ARTMAP , 2002, Neural Networks.
[75] Martin A. Riedmiller,et al. A direct adaptive method for faster backpropagation learning: the RPROP algorithm , 1993, IEEE International Conference on Neural Networks.
[76] Bernhard Sendhoff,et al. Generalization Improvement in Multi-Objective Learning , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.
[77] Leo Breiman,et al. Classification and Regression Trees , 1984 .
[78] Robert A. Jacobs,et al. Increased rates of convergence through learning rate adaptation , 1987, Neural Networks.
[79] James R. Williamson,et al. Gaussian ARTMAP: A Neural Network for Fast Incremental Learning of Noisy Multidimensional Maps , 1996, Neural Networks.
[80] Lester Ingber,et al. Simulated annealing: Practice versus theory , 1993 .
[81] Hisao Ishibuchi,et al. Single-objective and two-objective genetic algorithms for selecting linguistic rules for pattern classification problems , 1997, Fuzzy Sets Syst..
[82] Jong-Bae Park,et al. An Improved Particle Swarm Optimization for , 2010 .
[83] Gisbert Schneider,et al. Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training , 2006, BMC Bioinformatics.
[84] Kiyong Choi,et al. Parasitic-aware RF circuit design and optimization , 2004, IEEE Transactions on Circuits and Systems I: Regular Papers.
[85] Erol Gelenbe,et al. Traffic and video quality with adaptive neural compression , 1996, Multimedia Systems.
[86] Hussein A. Abbass,et al. Speeding Up Backpropagation Using Multiobjective Evolutionary Algorithms , 2003, Neural Computation.
[87] Biing-Hwang Juang,et al. Discriminative learning for minimum error classification [pattern recognition] , 1992, IEEE Trans. Signal Process..
[88] Erol Gelenbe,et al. Simulation with learning agents , 2001, Proc. IEEE.
[89] J.R. Artalejo,et al. G-networks: A versatile approach for work removal in queueing networks , 2000, Eur. J. Oper. Res..
[90] Erol Gelenbe,et al. Random Neural Networks with Negative and Positive Signals and Product Form Solution , 1989, Neural Computation.
[91] Chia-Feng Juang,et al. A hybrid of genetic algorithm and particle swarm optimization for recurrent network design , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[92] Mansooreh Mollaghasemi,et al. An Adaptive Multiobjective Approach to Evolving ART Architectures , 2010, IEEE Transactions on Neural Networks.
[93] C. Hubert,et al. Pattern completion with the random neural network using the RPROP learning algorithm , 1993, Proceedings of IEEE Systems Man and Cybernetics Conference - SMC.
[94] Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
[95] Erol Gelenbe,et al. Random Neural Networks with Multiple Classes of Signals , 1999, Neural Computation.
[96] Michael Georgiopoulos,et al. Fuzzy ART properties , 1995, Neural Networks.
[97] Georgios Loukas,et al. A Biologically Inspired pired Denial of Service Detector Using the Random Neural Network , 2007, 2007 IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems.
[98] Gerardo Rubino,et al. Performance evaluation of real-time speech through a packet network: a random neural networks-based approach , 2004, Perform. Evaluation.
[99] Bernhard Sendhoff,et al. Pareto-Based Multiobjective Machine Learning: An Overview and Case Studies , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[100] Ju-Jang Lee,et al. Training Two-Layered Feedforward Networks With Variable Projection Method , 2008, IEEE Transactions on Neural Networks.
[101] Georgios C. Anagnostopoulos,et al. Novel approaches in adaptive resonance theory for machine learning , 2001 .
[102] Gerardo Rubino,et al. A study of real-time packet video quality using random neural networks , 2002, IEEE Trans. Circuits Syst. Video Technol..
[103] Erol Gelenbe,et al. Stability of the Random Neural Network Model , 1990, Neural Computation.
[104] Jonathan E. Fieldsend,et al. Multi-class ROC analysis from a multi-objective optimisation perspective , 2006, Pattern Recognit. Lett..
[105] Carlos A. Coello Coello,et al. Evolutionary multi-objective optimization: a historical view of the field , 2006, IEEE Comput. Intell. Mag..
[106] Lifeng Xi,et al. An Improved Particle Swarm Optimization for Evolving Feedforward Artificial Neural Networks , 2007, Neural Processing Letters.
[107] Stelios Timotheou. Nonnegative Least Squares Learning for the Random Neural Network , 2008, ICANN.
[108] Erol Gelenbe,et al. Matched neural filters for EMI based mine detection , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).
[109] Moncef Gabbouj,et al. Evolutionary artificial neural networks by multi-dimensional particle swarm optimization , 2009, Neural Networks.
[110] Erol Gelenbe,et al. Synchronized Interactions in Spiked Neuronal Networks , 2008, Comput. J..
[111] Hans-Michael Voigt,et al. Soft Genetic Operators in Evolutionary Algorithms , 1995, Evolution and Biocomputation.
[112] Erol Gelenbe,et al. Steps toward self-aware networks , 2009, CACM.
[113] Teresa B. Ludermir,et al. Particle Swarm Optimization of Neural Network Architectures and Weights , 2007 .
[114] Stephen Grossberg,et al. Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps , 1992, IEEE Trans. Neural Networks.
[115] Arjen van Ooyen,et al. Improving the convergence of the back-propagation algorithm , 1992, Neural Networks.
[116] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[117] Juan Julián Merelo Guervós,et al. Evolving Multilayer Perceptrons , 2000, Neural Processing Letters.
[118] R. Eberhart,et al. Fuzzy adaptive particle swarm optimization , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).
[119] Erol Gelenbe,et al. Random Neural Networks with Synchronized Interactions , 2008, Neural Computation.
[120] E. Gelenbe. Product-form queueing networks with negative and positive customers , 1991 .
[121] Michael Georgiopoulos,et al. Order of Search in Fuzzy ART and Fuzzy ARTMAP: Effect of the Choice Parameter , 1996, Neural Networks.
[122] Stelios Timotheou,et al. The Random Neural Network: A Survey , 2010, Comput. J..
[123] Yu Wang,et al. Adaptive Inertia Weight Particle Swarm Optimization , 2006, ICAISC.
[124] Xin Yao,et al. Evolving artificial neural networks , 1999, Proc. IEEE.
[125] Taskin Koçak,et al. Design and implementation of a random neural network routing engine , 2003, IEEE Trans. Neural Networks.
[126] Erol Gelenbe,et al. The Random Neural Network Model for Texture Generation , 1992, Int. J. Pattern Recognit. Artif. Intell..
[127] Erol Gelenbe,et al. Design and performance of cognitive packet networks , 2001, Perform. Evaluation.
[128] Antoniya Georgieva,et al. Neural Network Learning With Global Heuristic Search , 2007, IEEE Transactions on Neural Networks.
[129] Anastasios N. Venetsanopoulos,et al. Fast learning algorithms for neural networks , 1992 .
[130] Erol Gelenbe,et al. Random Neural Network Recognition of Shaped Objects in Strong Clutter , 1997, ICANN.
[131] Mohammad Bagher Menhaj,et al. Training feedforward networks with the Marquardt algorithm , 1994, IEEE Trans. Neural Networks.
[132] David E. Goldberg,et al. Genetic Algorithms in Search Optimization and Machine Learning , 1988 .
[133] Erol Gelenbe,et al. Learning in the multiple class random neural network , 2002, IEEE Trans. Neural Networks.
[134] Khaled F. Hussain,et al. Laser intensity vehicle classification system based on random neural network , 2005, ACM-SE 43.
[135] Laxmidhar Behera,et al. On Adaptive Learning Rate That Guarantees Convergence in Feedforward Networks , 2006, IEEE Transactions on Neural Networks.