A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Exact calculation of the Hessian matrix for the multilayer perceptron
Neural Computation
Fast exact multiplication by the Hessian
Neural Computation
Training neural nets through stochastic minimization
Neural Networks
Boosting a weak learning algorithm by majority
Information and Computation
Pattern classification: a unified view of statistical and neural approaches
Pattern classification: a unified view of statistical and neural approaches
Handbook of mathematics (3rd ed.)
Handbook of mathematics (3rd ed.)
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
On the Discriminatory Power of Adaptive Feed-Forward Layered Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ridge Regression Learning Algorithm in Dual Variables
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
DeEPs: A New Instance-Based Lazy Discovery and Classification System
Machine Learning
Benchmarking a Reduced Multivariate Polynomial Pattern Classifier
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Discriminative Learning Framework with Pairwise Constraints for Video Object Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Classification-based objective functions
Machine Learning
Learning Algorithms for Nonparametric Solution to the Minimum Error Classification Problem
IEEE Transactions on Computers
Neural networks for classification: a survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Neural classifiers and statistical pattern recognition: applications for currently established links
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Classification ability of single hidden layer feedforward neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
A novel radial basis function neural network for discriminant analysis
IEEE Transactions on Neural Networks
Universal approximation using incremental constructive feedforward networks with random hidden nodes
IEEE Transactions on Neural Networks
Pruning and regularization in reservoir computing
Neurocomputing
Realtime training on mobile devices for face recognition applications
Pattern Recognition
Incremental face recognition for large-scale social network services
Pattern Recognition
Weighted extreme learning machine for imbalance learning
Neurocomputing
An online learning network for biometric scores fusion
Neurocomputing
A study on the randomness reduction effect of extreme learning machine with ridge regression
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part I
Comparison of different approaches to visual terrain classification for outdoor mobile robots
Pattern Recognition Letters
Boosting weighted ELM for imbalanced learning
Neurocomputing
Weighted Online Sequential Extreme Learning Machine for Class Imbalance Learning
Neural Processing Letters
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This letter presents a minimum classification error learning formulation for a single-layer feedforward network (SLFN). By approximating the nonlinear counting step function using a quadratic function, the classification error rate is shown to be deterministically solvable. Essentially the derived solution is related to an existing weighted least-squares method with class-specific weights set according to the size of data set. By considering the class-specific weights as adjustable parameters, the learning formulation extends the classification robustness of the SLFN without sacrificing its intrinsic advantage of being a closed-form algorithm. While the method is applicable to other linear formulations, our empirical results indicate SLFN's effectiveness on classification generalization.