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Compression and Machine Learning: A New Perspective on Feature Space Vectors
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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An Introduction to Kolmogorov Complexity and Its Applications
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An Introduction to Kolmogorov Complexity and Its Applications
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Term-weighting approaches in automatic text retrieval
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Introduction to Data Compression
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Kernel Methods for Pattern Analysis
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An Empirical Study of Two Approaches to Sequence Learning for Anomaly Detection
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Language Trees and Zipping
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Text mining: a new frontier for lossless compression
inferredcites →https://doi.org/10.1109/dcc.2000.838202openalex-snapshot
Text categorization using compression models
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Genomic analysis using methods from information theory
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A Technique for High-Performance Data Compression
inferredcites →https://doi.org/10.1109/tcom.1984.1096090openalex-snapshot
Data Compression Using Adaptive Coding and Partial String Matching
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A universal algorithm for sequential data compression
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Shared Information and Program Plagiarism Detection
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Towards parameter-free data mining
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Book Review: An introduction to Kolmogorov Complexity and its Applications Second Edition, 1997 by Ming Li and Paul Vitanyi (Springer (Graduate Text Series))
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Algorithmic Clustering of Music Based on String Compression
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Introduction to Information Theory and Data Compression
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A Minimum Description Length Principle for Perception
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