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On the Stochastic Complexity of Learning Realizable and Unrealizable Rules

https://doi.org/10.1007/bf00996271
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/0-387-34239-7openalex-snapshot
Estimation of Dependences Based on Empirical Data
inferredcites →https://doi.org/10.1007/978-3-642-61310-4_2openalex-snapshot
Asymptotic Methods in Analysis
inferredcites →https://doi.org/10.1007/bf00114010openalex-snapshot
Rigorous learning curve bounds from statistical mechanics
inferredcites →https://doi.org/10.1007/bf00993163openalex-snapshot
Bounds on the sample complexity of Bayesian learning using information theory and the VC dimension
inferredcites →https://doi.org/10.1016/0022-0000(92)90039-lopenalex-snapshot
Feedforward nets for interpolation and classification
inferredcites →https://doi.org/10.1016/0378-4371(93)90571-kopenalex-snapshot
Data compression and prediction in neural networks
inferredcites →https://doi.org/10.1016/0893-6080(89)90020-8openalex-snapshot
Multilayer feedforward networks are universal approximators
inferredcites →https://doi.org/10.1016/b978-0-08-094829-4.50020-9openalex-snapshot
A Statistical Approach to Learning and Generalization in Layered Neural Networks
inferredcites →https://doi.org/10.1016/b978-1-55860-213-7.50011-0openalex-snapshot
Calculation of the Learning Curve of Bayes Optimal Classification Algorithm for Learning a Perceptron With Noise
inferredcites →https://doi.org/10.1023/a:1022698821832openalex-snapshot
Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension
inferredcites →https://doi.org/10.1063/1.2811676openalex-snapshot
Spin Glass Theory and Beyond
inferredcites →https://doi.org/10.1103/physreva.45.4102openalex-snapshot
Learning unlearnable problems with perceptrons
inferredcites →https://doi.org/10.1103/physreva.45.6056openalex-snapshot
Statistical mechanics of learning from examples
inferredcites →https://doi.org/10.1103/physreva.45.8874openalex-snapshot
Calculation of learning curves for inconsistent algorithms
inferredcites →https://doi.org/10.1103/revmodphys.65.499openalex-snapshot
The statistical mechanics of learning a rule
inferredcites →https://doi.org/10.1109/5.58339openalex-snapshot
A statistical approach to learning and generalization in layered neural networks
inferredcites →https://doi.org/10.1142/0271openalex-snapshot
Spin Glass Theory and Beyond
inferredcites →https://doi.org/10.1145/180139.181018openalex-snapshot
Rigorous learning curve bounds from statistical mechanics
inferredcites →https://doi.org/10.1162/neco.1992.4.4.605openalex-snapshot
Four Types of Learning Curves
inferredcites →https://doi.org/10.1162/neco.1993.5.1.140openalex-snapshot
Statistical Theory of Learning Curves under Entropic Loss Criterion
inferredcites →https://doi.org/10.1214/aos/1176350051openalex-snapshot
Stochastic Complexity and Modeling
inferredcites →https://doi.org/10.2307/2312103openalex-snapshot
Principles of Neurodynamics.
inferredcites →https://doi.org/10.2307/2988246openalex-snapshot
Estimation of Dependences Based on Empirical Data.
inferredcites →https://doi.org/10.5555/114836.114844openalex-snapshot
Calculation of the learning curve of Bayes optimal classification algorithm for learning a perceptron with noise

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/3-540-63246-8_13openalex-snapshot
Metric entropy and minimax risk in classification
inferred← citeshttps://doi.org/10.1007/978-3-540-27819-1_23openalex-snapshot
Suboptimal Behavior of Bayes and MDL in Classification Under Misspecification
inferred← citeshttps://doi.org/10.1007/s10849-005-9004-8openalex-snapshot
Bayesian Model Learning Based on Predictive Entropy
inferred← citeshttps://doi.org/10.1007/s10994-007-0716-7openalex-snapshot
Suboptimal behavior of Bayes and MDL in classification under misspecification
inferred← citeshttps://doi.org/10.1016/s0025-5564(01)00096-7openalex-snapshot
Bayesian predictiveness, exchangeability and sufficientness in bacterial taxonomy
inferred← citeshttps://doi.org/10.1016/s0893-6080(01)00069-7openalex-snapshot
Algebraic geometrical methods for hierarchical learning machines
inferred← citeshttps://doi.org/10.1088/0305-4470/29/17/014openalex-snapshot
Finite-size effects in Bayesian model selection and generalization
inferred← citeshttps://doi.org/10.1103/physrevlett.75.3772openalex-snapshot
Bounds for Predictive Errors in the Statistical Mechanics of Supervised Learning
inferred← citeshttps://doi.org/10.1109/18.720534openalex-snapshot
Universal prediction
inferred← citeshttps://doi.org/10.1214/aos/1030741081openalex-snapshot
Mutual information, metric entropy and cumulative relative entropy risk
inferred← citeshttps://doi.org/10.48550/arxiv.math/0406221openalex-snapshot
Suboptimal behaviour of Bayes and MDL in classification under misspecification
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