ML Anthology
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24 papers
Analogical Logic Program Synthesis Algorithm That Can Refute Inappropriate Similarities
Ken Sadohara, Makoto Haraguchi
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Application of Kolmogorov Complexity to Inductive Inference with Limited Memory
Andris Ambainis
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Complexity of Network Training for Classes of Neural Networks
Charles C. Pinter
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Efficient Learning of Real Time One-Counter Automata
Amr F. Fahmy, Robert S. Roos
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Grammatical Inference: An Old and New Paradigm
Yasubumi Sakakibara
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Incremental Learning of Logic Programs
M. R. K. Krishna Rao
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Inductive Constraint Logic
Luc De Raedt, Wim Van Laer
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Inferring a DNA Sequence from Erroneous Copies (Abstract)
John D. Kececioglu, Ming Li, John Tromp
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Language Learning from Membership Queries and Characteristic Examples
Hiroshi Sakamoto
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Learning Nested Differences in the Presence of Malicious Noise
Peter Auer
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Learning Ordered Binary Decision Diagrams
Ricard Gavaldà, David Guijarro
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Learning Orthogonal F-Horn Formulas
Akira Miyashiro, Eiji Takimoto, Yoshifumi Sakai, Akira Maruoka
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Learning Sparse Linear Combinations of Basis Functions over a Finite Domain
Atsuyoshi Nakamura, Shinji Miura
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Learning Strongly Deterministic Even Linear Languages from Positive Examples
Takeshi Koshiba, Erkki Mäkinen, Yuji Takada
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Learning Unions of Tree Patterns Using Queries
Hiroki Arimura, Hiroki Ishizaka, Takeshi Shinohara
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Machine Induction Without Revolutionary Paradigm Shifts
John Case, Sanjay Jain, Arun Sharma
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Noisy Inference and Oracles
Frank Stephan
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On Approximately Identifying Concept Classes in the Limit
Satoshi Kobayashi, Takashi Yokomori
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Probabilistic Language Learning Under Monotonicity Constraints
Léa Meyer
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Reflecting and Self-Confident Inductive Inference Machines
Klaus P. Jantke
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Simple PAC Learning of Simple Decision Lists
Jorge Castro, José L. Balcázar
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Simulating Teams with Many Conjectures
Bala Kalyanasundaram, Mahendran Velauthapillai
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Technical and Scientific Issues of KDD (or: Is KDD a Science?)
Yves Kodratoff
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The Complexity of Learning Minor Closed Graph Classes
Carlos Domingo, John Shawe-Taylor
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