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Steering self-learning distance algorithms

Published: 01 November 2009 Publication History
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References

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Ailon, N., Chazelle, B., Comandur, S., and Liu, D. Self-improving algorithms. In Proceedings of the 17th ACM-SIAM Symposium on Discrete Algorithms (SIAM press, Philadelphia, PA), 261--270, 2006.
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Bar-Hillel, A., and Weinshall, D. Learning distance function by coding similarity. In Proceedings of 24th International Conference on Machine Learning (Madison, WI, 2007), Omnipress, 65--72.
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Basu, S., Davidson, I., and Wagstaff, K. Constrained Clustering: Advances in Algorithms, Theory and Applications, Chapman&Hall/CRC, 2008.
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Csiszár, I. Why least squares and maximum entropy? An axiomatic approach to inference for linear inverse problems. Annals of Statistics 19, 4, (1991) 2032--2066.
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Deza, E., Deza, M. M. Dictionary of distances, Elsevier, 2006.
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Goldberg, D., Nichols, D., Oki, B. M., and Terry, D. Using collaborative filtering to weave an information tapestry. Comm. ACM 35, 12, (Dec. 1992), 61--70.
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Hertz, T. Learning distance functions: Algorithms and applications. PhD thesis, 2006.
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Liu, Y., Zha, H., and Qin, H. Shape topics: A compact representation and new algorithms for 3D partial shape retrieval. In Proceedings of IEEE Computer Vision and Pattern Recognition Conference (CA 2006), 2025--2032.
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  • (2017)Distance selection based on relevance feedback in the context of CBIR using the SFS meta-heuristic with one roundEgyptian Informatics Journal10.1016/j.eij.2016.09.00118:1(1-9)Online publication date: Mar-2017

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    Steering self-learning distance algorithms

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      cover image Communications of the ACM
      Communications of the ACM  Volume 52, Issue 11
      Scratch Programming for All
      November 2009
      135 pages
      ISSN:0001-0782
      EISSN:1557-7317
      DOI:10.1145/1592761
      Issue’s Table of Contents
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Publication History

      Published: 01 November 2009
      Published in CACM Volume 52, Issue 11

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      • (2017)Distance selection based on relevance feedback in the context of CBIR using the SFS meta-heuristic with one roundEgyptian Informatics Journal10.1016/j.eij.2016.09.00118:1(1-9)Online publication date: Mar-2017

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