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A Framework for Average Case Analysis of Conjunctive Learning Algorithms
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Probably Approximately Correct Learning
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On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
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Explanation-Based Learning: An Alternative View
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Knowledge Acquisition Via Incremental Conceptual Clustering
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Learning nested differences of intersection-closed concept classes
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Implementing Valiant's Learnability Theory Using Random Sets
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Generalization as search
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Quantitative results concerning the utility of explanation-based learning
inferredcites →https://doi.org/10.1016/b978-0-934613-03-3.50040-4openalex-snapshot
Generalization as Search
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Bias, Version Spaces and Valiant's Learning Framework
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Learning Internal Representations by Error Propagation
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ONE-SIDED ALGORITHMS FOR INTEGRATING EMPIRICAL AND EXPLANATION-BASED LEARNING
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COMBINING EMPIRICAL AND ANALYTICAL LEARNING WITH VERSION SPACES
inferredcites →https://doi.org/10.1016/b978-1-55860-036-2.50026-6openalex-snapshot
Explanation-based learning with weak domain theories
inferredcites →https://doi.org/10.1016/b978-1-55860-247-2.50031-0openalex-snapshot
Average Case Analysis of Learning k-CNF Concepts
inferredcites →https://doi.org/10.1023/a:1022689616458openalex-snapshot
Toward a Unified Science of Machine Learning
inferredcites →https://doi.org/10.1023/a:1022696716689openalex-snapshot
Learning Nested Differences of Intersection-Closed Concept Classes
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Statistical principles in experimental design.
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An Introduction to Mathematical Learning Theory
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Nearest neighbor pattern classification
inferredcites →https://doi.org/10.1137/1116025openalex-snapshot
On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
inferredcites →https://doi.org/10.1145/28395.28426openalex-snapshot
On the learnability of Boolean formulae
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Learnability and the Vapnik-Chervonenkis dimension
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Learning Internal Representations by Error Propagation
inferredcites →https://doi.org/10.2172/6731854openalex-snapshot
Implementation of Valiant's learnability theory using random sets
inferredcites →https://doi.org/10.2307/1419292openalex-snapshot
Statistical Principles in Experimental Design
inferredcites →https://doi.org/10.2307/1420401openalex-snapshot
An Introduction to Mathematical Learning Theory
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Creating A Memory of Causal Relationships
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Learnability by fixed distributions
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Quantitative Results Concerning the Utility of Explanation-Based Learning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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A Complete and Tight Average-Case Analysis of Learning Monomials
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Average case analysis of a learning algorithm for μ-DNF expressions
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An average predictive accuracy of the nearest neighbor classifier
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An average-case analysis of k-nearest neighbor classifier
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Theoretical analysis of case retrieval method based on neighborhood of a new problem
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Towards the Discovery of Reliable Biomarkers from Gene-Expression Profiles: An Iterative Constraint Satisfaction Learning Approach
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Automated Refinement of First-Order Horn-Clause Domain Theories
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Selection of relevant features and examples in machine learning
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Effects of domain characteristics on instance-based learning algorithms
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Case-based learning of plans and goal states in medical diagnosis
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A simulated annealing technique for generating artificial data to assess concept learning algorithms
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Annotated bibliography on research methodologies
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Review of "Inductive Logic Programming: Techniques and Applications" by Nada Lavrač, Sašo Džeroski
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Learning Controllers for Industrial Robots
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A Reply to Cohen's Book Review of Creating a Memory of Causal Relationships
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Learning Causal Patterns: Making a Transition from Data-Driven to Theory-Driven Learning
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Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension
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Rigorous Learning Curve Bounds from Statistical Mechanics
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Density functionals and Kohn-Sham potentials with minimal wavefunction preparations on a quantum computer
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Hamming Distance Computation in Unreliable Resistive Memory
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Rigorous learning curve bounds from statistical mechanics
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A Novel Bayesian Entropy Network for Probabilistic Damage Detection and Classification
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