Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and the bias/variance dilemma
Neural Computation
A practical Bayesian framework for backpropagation networks
Neural Computation
SIAM Journal on Numerical Analysis
A limited memory algorithm for bound constrained optimization
SIAM Journal on Scientific Computing
Neural networks: a systematic introduction
Neural networks: a systematic introduction
Principal component neural networks: theory and applications
Principal component neural networks: theory and applications
The new ERA in supervised learning
Neural Networks
Regularization with a pruning prior
Neural Networks
Weight decay backpropagation for noisy data
Neural Networks
Constructive incremental learning from only local information
Neural Computation
Pruning using parameter and neuronal metrics
Neural Computation
No free lunch for early stopping
Neural Computation
Evaluating derivatives: principles and techniques of algorithmic differentiation
Evaluating derivatives: principles and techniques of algorithmic differentiation
Ensemble learning via negative correlation
Neural Networks
Nonmonotone and monotone active-set methods for image restoration, part 1: convergence analysis
Journal of Optimization Theory and Applications
Nonomotone and monoton active-set methods for image restoration, Part 2: numerical results
Journal of Optimization Theory and Applications
Bayesian Learning for Neural Networks
Bayesian Learning for Neural Networks
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Building blocks for odd—even multigrid with applications reduced to systems
Journal of Computational and Applied Mathematics
Meta-Heuristics: Theory and Applications
Meta-Heuristics: Theory and Applications
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks
Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
A Dozen Tricks with Multitask Learning
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
Solving the Ill-Conditioning in Neural Network Learning
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
A Simple Trick for Estimating the Weight Decay Parameter
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
Reduction and Refinement Strategies for Probabilistic Analysis
PAPM-PROBMIV '02 Proceedings of the Second Joint International Workshop on Process Algebra and Probabilistic Methods, Performance Modeling and Verification
Square Unit Augmented, Radially Extended, Multilayer Perceptrons
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
Second-Order Learning Algorithm with Squared Penalty Term
Neural Computation
Nonlinear Autoassociation Is Not Equivalent to PCA
Neural Computation
The dependence identification neural network construction algorithm
IEEE Transactions on Neural Networks
Robust error measure for supervised neural network learning with outliers
IEEE Transactions on Neural Networks
Contrast enhancement for backpropagation
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Exploring and comparing the best “direct methods” for the efficient training of MLP-networks
IEEE Transactions on Neural Networks
Neural and statistical classifiers-taxonomy and two case studies
IEEE Transactions on Neural Networks
Capabilities of a four-layered feedforward neural network: four layers versus three
IEEE Transactions on Neural Networks
High-order and multilayer perceptron initialization
IEEE Transactions on Neural Networks
Robust Formulations for Training Multilayer Perceptrons
Neural Computation
Ideas about a regularized MLP classifier by means of weight decay stepping
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
A neural network experiment on the site-specific simulation of potato tuber growth in Eastern Canada
Computers and Electronics in Agriculture
Neural prediction of product quality based on pilot paper machine process measurements
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part I
A quantitative comparison of different MLP activation functions in classification
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
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A simple and general calculus for the sensitivity analysis of a feedforward MLP network in a layer-wise form is presented. Based on the local optimality conditions, some consequences for the least-means-squares learning problem are stated and further discussed. Numerical experiments with formulation and comparison of different weight decay techniques are included.