Genetic Programming Bibliography entries for Paul M B Vitanyi

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GP coauthors/coeditors: Rudi Cilibrasi, Ronald de Wolf, Andrew R Cohen, Cristina Maria Nogueira da Costa Santos, Joao Bernardes, Luis Filipe Coelho Antunes,

Genetic Programming Articles by Paul M B Vitanyi

1. Andrew R. Cohen and Paul M. B. Vitanyi. Normalized Compression Distance of Multisets with Applications. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(8):1602-1614, 2015. details

2. Paul M. B. Vitanyi. Similarity and denoising. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 371(1984) 2013. details

3. Rudi L. Cilibrasi and Paul M. B. Vitanyi. The Google Similarity Distance. IEEE Transactions on Knowledge and Data Engineering, 19(3):370-383, 2007. details

4. P. Vitanyi. Asshuku ni Motozuita Hanyou na Ruijido Sokuteihou. Surikagaku, 2006. Japanese, translated by O. Watanabe, English title: Universal similarity based on compression. details

5. Rudi Cilibrasi and Paul M. B. Vitanyi. Clustering by Compression. IEEE Transactions on Information Theory, 51(4):1523-1545, 2005. details

6. Rudi Cilibrasi and Paul Vitanyi and Ronald de Wolf. Algorithmic Clustering of Music Based on String Compression. Computer Music Journal, 28(4):49-67, 2004. details

7. Paul Vitanyi. A discipline of evolutionary programming. Theoretical Computer Science, 241(1--2):3-23, 2000. details

Genetic Programming conference papers by Paul M B Vitanyi

• C. C. Santos and J. Bernardes and P. M. B. Vitanyi and L. Antunes. Clustering Fetal Heart Rate Tracings by Compression. In 19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06), pages 685-690, Salt Lake City, UT, USA, 2006. details

• Rudi Cilibrasi and Paul Vitanyi. A New Quartet Tree Heuristic for Hierarchical Clustering. In Principled methods of trading exploration and exploitation Workshop, London, 2005. details

Genetic Programming other entries for Paul M B Vitanyi

• Rudi Cilibrasi and Paul M. B. Vitanyi. Automatic Meaning Discovery Using Google. 2005. v2. details