Neural Networks and the Bias/Variance Dilemma

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The Quantitative Evaluation of Functional Neuroimaging Experiments: Mutual Information Learning Curves

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Ensemble Methods

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Adaptive Thinking

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Generalisation error in learning with random features and the hidden manifold model*

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Bias in Machine Learning: A Literature Review

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Neural Network Classification and Prior Class Probabilities

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Why Is Optimization Difficult?

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Investigation of the CasCor Family of Learning Algorithms

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Differential Evolution algorithms applied to Neural Network training suffer from stagnation

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Network performance assessment for Neurofuzzy data modelling

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Bias/Variance Decompositions for Likelihood-Based Estimators

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The DOP Estimation Method Is Biased and Inconsistent

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Using machine learning approach for microseismic events recognition in underground excavations: Comparison of ten frequently-used models

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Evolutionary Induction of Sparse Neural Trees

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Innateness, AlphaZero, and Artificial IntelligencePreprint

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Toward Personalized Activity Recognition Systems With a Semipopulation Approach

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When behaviour reveals activity: Assigning fishing effort to métiers based on VMS data using artificial neural networks

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Boosting Regression Estimators

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Perceptron: Learning, Generalization, Model Selection, Fault Tolerance, and Role in the Deep Learning Era

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Satisficing: Integrating Two Traditions

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LSHiForest: A Generic Framework for Fast Tree Isolation Based Ensemble Anomaly Analysis

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Early stopping by correlating online indicators in neural networks

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VIEW~~~~~~~~~~~~~~ ~ Communicated by Lawrence Jackel Neural Networks and the Bias/Variance Dilemma

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Neural Networks and the BiadVariance Dilemma

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VIEW Communicated by Lawrence Jackel Neural Networks and the BiadVariance Dilemma

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