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Using the Minimum Description Length Principle to Infer Reduced Ordered Decision Graphs
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Verification of synchronous sequential machines based on symbolic execution
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The complexity of the optimal variable ordering problems of shared binary decision diagrams
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Logic Minimization Algorithms for VLSI Synthesis
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Dynamic Variable Ordering for Ordered Binary Decision Diagrams
inferredcites →https://doi.org/10.1007/978-1-4757-3860-5openalex-snapshot
An Introduction to Kolmogorov Complexity and Its Applications
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An Introduction to Kolmogorov Complexity and Its Applications
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Boolean feature discovery in empirical learning
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Modified Branching Programs and Their Computational Power
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Modeling by shortest data description
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Inferring decision trees using the minimum description lenght principle
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Fringe-Like Feature Construction: A Comparative Study and a Unifying Scheme
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A Conservation Law for Generalization Performance
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Supervised and Unsupervised Discretization of Continuous Features
inferredcites →https://doi.org/10.1023/a:1022611825350openalex-snapshot
Boolean Feature Discovery in Empirical Learning
inferredcites →https://doi.org/10.1080/03081077808960690openalex-snapshot
ON THE CONNECTION BETWEEN THE COMPLEXITY AND CREDIBILITY OF INFERRED MODELS
inferredcites →https://doi.org/10.1093/oso/9780198555520.003.0001openalex-snapshot
Statistical Inference
inferredcites →https://doi.org/10.1109/12.53586openalex-snapshot
Finding the optimal variable ordering for binary decision diagrams
inferredcites →https://doi.org/10.1109/dac.1990.114826openalex-snapshot
Efficient implementation of a BDD package
inferredcites →https://doi.org/10.1109/ee.1938.6431064openalex-snapshot
A symbolic analysis of relay and switching circuits
inferredcites →https://doi.org/10.1109/iccad.1991.185307openalex-snapshot
Minimization of binary decision diagrams based on exchanges of variables
inferredcites →https://doi.org/10.1109/t-aiee.1938.5057767openalex-snapshot
A symbolic analysis of relay and switching circuits
inferredcites →https://doi.org/10.1109/tc.1986.1676819openalex-snapshot
Graph-Based Algorithms for Boolean Function Manipulation
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Classifying learnable geometric concepts with the Vapnik-Chervonenkis dimension
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Efficient implementation of a BDD package
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Heuristic minimization of BDDs using don't cares
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Stochastic Complexity and Modeling
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Machine Learning: A Comparative Study of Pattern Theory and C4.5
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Dynamic variable ordering for ordered binary decision diagrams
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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An implicit formulation for exact BDD minimization of incompletely specified functions
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An Efficient Private Evaluation of a Decision Graph
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Techniques of Decision Tree Induction
inferred← citeshttps://doi.org/10.1007/978-3-540-24581-0_23openalex-snapshot
MML Inference of Decision Graphs with Multi-way Joins and Dynamic Attributes
inferred← citeshttps://doi.org/10.1007/978-3-642-21738-8_40openalex-snapshot
Top-Down Induction of Reduced Ordered Decision Diagrams from Neural Networks
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A beam search algorithm for PFSA inference
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Decision diagrams in machine learning: an empirical study on real-life credit-risk data
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A decision graph explanation of protein secondary structure prediction
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Efficient Coding of Labelled Graphs
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Circuit Learning: From Decision Trees to Decision Graphs
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Optimizing Binary Decision Diagrams for Interpretable Machine Learning Classification
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NOW G-Net: learning classification programs on networks of workstations
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Extracting Rules From Neural Networks as Decision Diagrams
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SONGs: Self-Organizing Neural Graphs
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Inductive Inference by Using Information Compression
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Optimal Decision Diagrams for Classification
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On the use of multi-objective evolutionary algorithms for classification rule induction
inferred← citeshttps://doi.org/10.17771/pucrio.acad.64308openalex-snapshot
DECISION DIAGRAMS FOR CLASSIFICATION: NEW CONSTRUCTIVE APPROACHES
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Learning understandable classifier models.
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On Efficiently Explaining Graph-Based Classifiers
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SONG: Self-Organizing Neural Graphs
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Unsupervised Learning in a Framework of Information Compression by Multiple Alignment, Unification and Search
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Unsupervised Grammar Induction in a Framework of Information Compression by Multiple Alignment, Unification and Search
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Unifying Computing and Cognition: The SP Theory and its Applications
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