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Locality-preserving hashing in multidimensional spaces

Authors:

Piotr Indyk,

Rajeev Motwani,

Prabhakar Raghavan,

Santosh VempalaAuthors Info & Claims

STOC '97: Proceedings of the twenty-ninth annual ACM symposium on Theory of computing

Pages 618 - 625

https://doi.org/10.1145/258533.258656

Published: 04 May 1997 Publication History

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References

[1]

P.K. Agarwal and J. Matousek, "Ray shooting and parametric search," Proc. 2jth STOC (1992), 517 - 526.

Digital Library

Google Scholar

[2]

S. Arya, D. M. Mount, N.S. Netanyahu, R. Silverman, A. Wu, "An optimal algorithm for approximate nearest neighbor searching," Proc. 5th SODA (1994), pp. 573 - 582.

Digital Library

Google Scholar

[3]

C. Buckley, A. Singhal, M. Mitra, and G. Salton, New Retrieval Approaches Using SMART: TREC 4. Proc. Fourth Text Retrieval Conference, National Institute of Standards and Technology, 1995.

Google Scholar

[4]

K. Clarkson, "A randomized algorithm for closest-point queries," SIAM J. Computing, 17 (1988), pp. 830-847.

Digital Library

Google Scholar

[5]

S. Cost and S. Salzberg, "A weighted nearest neighbor algorithm for learning with symbolic features," Machine Learning, 10 (1993), pp. 57-67.

Digital Library

Google Scholar

[6]

T.M. (:over and P.E. Hart, "Nearest neighbor pattern classification," iEEE Transactions on information Theory, 13 (1967), pp. 21-27.

Google Scholar

[7]

S. Deerwester, S. T. Dumais, T.K. Landauer, G.W. Furnas, and R.A. Harshman, "Indexing by latent semantic analysis," Journal of the Society for Information Science, 41 (1990), pp. 391-407.

Crossref

Google Scholar

[8]

L. Devroye and T.J. Wagner, "Nearest neighbor methods in discrimination," Handbook of Statistics, vol. 2, P.R. Krishnaiah, L.N. Kanal, eds., North-Holland, 1982.

Google Scholar

[9]

D. Dobkin and R. Lipton, "Multidimensional search problems," SiAM J. Computing, 5 (1976), pp. 181-186.

Crossref

Google Scholar

[10]

R.O. Duda and P.E. Hart, Pattern Classification and Scene Analysis, Wiley, 1973.

Digital Library

Google Scholar

[11]

C,. Faloutsos, R. Barber, M. Flickner, W. Niblack, D. Petkovic and W. Equitz, "Efficient and effective querying by image content", Journal of Intelligent Information Systems, 3 (1994), pp. 231-262.

Digital Library

Google Scholar

[12]

A. Gersho and R.M. Gray, Vector Quantization and Signal Compression, Kluwer Academic, 1991.

Digital Library

Google Scholar

[13]

T. Hastie and R. Tibshirani, "Discriminant adaptive nearest neighbor classification," First International Conference on Knowledge Discovery and Data Mining, 1995.

Google Scholar

[14]

H. Hotelling, "Analysis of a complex of statistical variables into principal components", Journal of educational psychology, 27 (1933), pp. 417-441.

Crossref

Google Scholar

[15]

IEEE Computer Special Issue on Content. based Image Retrieval Systems, 28 (1995).

Google Scholar

[16]

K. Karhunen. Ober lineare Methoden in der Wahrscheinlichkeitsredmung. Ann. Acad. Sci. Fennicae, Ser. A137, 1947.

Google Scholar

[17]

J. Kleinberg, "Two algorithms for nearest-neighbor search in high dimensions", these proceedings.

Digital Library

Google Scholar

[18]

D. Knuth, The Art of Computer Programming, vol. 3, Sorting and Searching, Addison Wesley, 1973.

Digital Library

Google Scholar

[19]

E. Kreyszig, Introductory Functional Analysis with Applications, Wiley, 1989.

Google Scholar

[20]

V. Koivune and S. Kassam, "Nearest neighbor filters for multivariate data," IEEE Workshop on Nonlinear Signal and Image Processing, 1995.

Google Scholar

[21]

N. Linial and O. Sasson, Non-Expansive Hashing, In Proc. 28th STOC (1996), pp. 509-517.

Digital Library

Google Scholar

[22]

M. Lo~ve. Fonctions aleastoires de second ordere. Processus Stochastiques et mouvement Brownian. Hermann, Paris, 1948.

Google Scholar

[23]

J. Matousek, "Reporting points in halfspaces," Proc. 32nd FOGS, 1991.

Digital Library

Google Scholar

[24]

S. Meiser, "Point location in arrangements of hyperplanes," Information and Computation (1993), 106, 2, pp. 286-303.

Digital Library

Google Scholar

[25]

K. Mulmuley, "Randomized multi-dimensional search trees: further results in dynamic sampling," Proc. 32nd FOGS, 1991.

Digital Library

Google Scholar

[26]

Panel on Discriminant Analysis and Clustering, National Research Council, Discriminant Analysis and Clustering, National Academy Press, 1988.

Google Scholar

[27]

A. Pentland, R.W. Picard, and S. Sclaroff, "Photobook: tools for content-based manipulation of image databases", In Proc. SPIE Conference on Storage and Retrieval of Image and Video Databases II, 2185, 1994.

Google Scholar

[28]

G. Salton, Automatic Text Processing, Addison-Wesley, Reading, MA, 1989.

Digital Library

Google Scholar

[29]

H. Samet, The Design and Analysis of Spatial Data Structures, Addison-Wesley, Reading, MA, 1989.

Digital Library

Google Scholar

[30]

A.W.M. Smeulders and R. Jain, editors, Image Databases and Multi-media Search, Proceedings of the First International Workshop, IDB-MMS '96, Amsterdam. Amsterdam University Press, 1996.

Google Scholar

[31]

A.C. Yao and F.F. Yao, "A general approach to d-dimensional geometric queries," Proc. 17th STOC (1985), pp. 163- 168.

Digital Library

Google Scholar

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Yang YChen HLiu RLiu SZhan YHu CShi R(2024)DSCEH: Dual-Stream Correlation-Enhanced Deep Hashing for Image RetrievalMathematics10.3390/math1214222112:14(2221)Online publication date: 16-Jul-2024
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Ma WPeng YLiu XCui J(2024)VeriRange: A Verifiable Range Query Model on Encrypted Geographic Data for IoT EnvironmentIEEE Internet of Things Journal10.1109/JIOT.2023.329458911:2(3068-3081)Online publication date: 15-Jan-2024
https://doi.org/10.1109/JIOT.2023.3294589
He XLiu YHe H(2024)Accelerating similarity-based model matching using dual hashingSoftware and Systems Modeling10.1007/s10270-024-01173-1Online publication date: 29-Apr-2024
https://doi.org/10.1007/s10270-024-01173-1
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Locality-preserving hashing in multidimensional spaces

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STOC '97: Proceedings of the twenty-ninth annual ACM symposium on Theory of computing

May 1997

752 pages

ISBN:0897918886

DOI:10.1145/258533

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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Published: 04 May 1997

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STOC97: 29th Annual Symposium on Theory of Computing

May 4 - 6, 1997

Texas, El Paso, USA

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STOC '97 Paper Acceptance Rate 75 of 211 submissions, 36%;

Overall Acceptance Rate 1,469 of 4,586 submissions, 32%

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Yang YChen HLiu RLiu SZhan YHu CShi R(2024)DSCEH: Dual-Stream Correlation-Enhanced Deep Hashing for Image RetrievalMathematics10.3390/math1214222112:14(2221)Online publication date: 16-Jul-2024
https://doi.org/10.3390/math12142221
Ma WPeng YLiu XCui J(2024)VeriRange: A Verifiable Range Query Model on Encrypted Geographic Data for IoT EnvironmentIEEE Internet of Things Journal10.1109/JIOT.2023.329458911:2(3068-3081)Online publication date: 15-Jan-2024
https://doi.org/10.1109/JIOT.2023.3294589
He XLiu YHe H(2024)Accelerating similarity-based model matching using dual hashingSoftware and Systems Modeling10.1007/s10270-024-01173-1Online publication date: 29-Apr-2024
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Rabbani TBornstein MHuang FOh ANaumann TGloberson ASaenko KHardt MLevine S(2023)Large-scale distributed learning via private on-device locality-sensitive hashingProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3666833(16153-16171)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.5555/3666122.3666833
Rajput SMehta NSingh AKeshavan RVu THeidt LHong LTay YTran VSamost JKula MChi ESathiamoorthy MOh ANaumann TGloberson ASaenko KHardt MLevine S(2023)Recommender systems with generative retrievalProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3666574(10299-10315)Online publication date: 10-Dec-2023
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Wei RKerschbaum F(2023)Cryptographically Secure Private Record Linkage using Locality-Sensitive HashingProceedings of the VLDB Endowment10.14778/3626292.362629317:2(79-91)Online publication date: 1-Oct-2023
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Lall SRay SBandyopadhyay S(2022)A copula based topology preserving graph convolution network for clustering of single-cell RNA-seq dataPLOS Computational Biology10.1371/journal.pcbi.100960018:3(e1009600)Online publication date: 10-Mar-2022
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