Explanatory and creative alternatives to the MDL principle

DOI10.1023/A:1011350914776zbMath0973.68206OpenAlexW2124026090MaRDI QIDQ5938216

Ismael García-Varea, José Hernández-Orallo

Publication date: 2 September 2001

Published in: Foundations of Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/a:1011350914776

zbMATH Keywords

minimum description length

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Algorithmic information theory (Kolmogorov complexity, etc.) (68Q30) Foundations of classical theories (including reverse mathematics) (03B30)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Comparison of identification criteria for machine inductive inference
• Stochastic complexity and modeling
• Inferring decision trees using the minimum description length principle
• Modeling by shortest data description
• On the necessity of Occam algorithms
• A formal model of hierarchical concept learning
• Complexity-based induction
• Model selection based on minimum description length
• Queries and concept learning
• On the intrinsic complexity of learning
• Learnability and the Vapnik-Chervonenkis dimension
• A theory of the learnable
• Toward a mathematical theory of inductive inference
• Complexity-based induction systems: Comparisons and convergence theorems
• Inductive Logic Programming: Theory and methods
• Universal prediction
• The minimum description length principle in coding and modeling
• Fisher information and stochastic complexity
• Constructive reinforcement learning
• A Machine-Independent Theory of the Complexity of Recursive Functions
• An Information Measure for Classification
• Language identification in the limit
• A formal theory of inductive inference. Part II

This page was built for publication: Explanatory and creative alternatives to the MDL principle