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Order preserving hashing for approximate nearest neighbor search

Published: 21 October 2013 Publication History

Abstract

In this paper, we propose a novel method to learn similarity-preserving hash functions for approximate nearest neighbor (NN) search. The key idea is to learn hash functions by maximizing the alignment between the similarity orders computed from the original space and the ones in the hamming space. The problem of mapping the NN points into different hash codes is taken as a classification problem in which the points are categorized into several groups according to the hamming distances to the query. The hash functions are optimized from the classifiers pooled over the training points. Experimental results demonstrate the superiority of our approach over existing state-of-the-art hashing techniques.

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  • (2024)Entropy-Optimized Deep Weighted Product Quantization for Image RetrievalIEEE Transactions on Image Processing10.1109/TIP.2024.335906633(1162-1174)Online publication date: 2024
  • (2024)Anchor-based Domain Adaptive Hashing for unsupervised image retrievalInternational Journal of Machine Learning and Cybernetics10.1007/s13042-024-02298-x15:12(6011-6026)Online publication date: 21-Aug-2024
  • (2022)Deep Feature Pyramid Hashing for Efficient Image RetrievalInformation10.3390/info1401000614:1(6)Online publication date: 22-Dec-2022
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    cover image ACM Conferences
    MM '13: Proceedings of the 21st ACM international conference on Multimedia
    October 2013
    1166 pages
    ISBN:9781450324045
    DOI:10.1145/2502081
    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: 21 October 2013

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    Author Tags

    1. approximate nearest neighbor search
    2. learning to hash
    3. order preserving hashing

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    MM '13
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    MM '13: ACM Multimedia Conference
    October 21 - 25, 2013
    Barcelona, Spain

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    MM '13 Paper Acceptance Rate 47 of 235 submissions, 20%;
    Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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    • (2024)Entropy-Optimized Deep Weighted Product Quantization for Image RetrievalIEEE Transactions on Image Processing10.1109/TIP.2024.335906633(1162-1174)Online publication date: 2024
    • (2024)Anchor-based Domain Adaptive Hashing for unsupervised image retrievalInternational Journal of Machine Learning and Cybernetics10.1007/s13042-024-02298-x15:12(6011-6026)Online publication date: 21-Aug-2024
    • (2022)Deep Feature Pyramid Hashing for Efficient Image RetrievalInformation10.3390/info1401000614:1(6)Online publication date: 22-Dec-2022
    • (2022)Adversarial Binary Mutual Learning for Semi-Supervised Deep HashingIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2021.305583433:8(4110-4124)Online publication date: Aug-2022
    • (2022)Transductive Semisupervised Deep HashingIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2021.305438633:8(3713-3726)Online publication date: Aug-2022
    • (2022)Scalable Distributed Hashing for Approximate Nearest Neighbor SearchIEEE Transactions on Image Processing10.1109/TIP.2021.313052831(472-484)Online publication date: 2022
    • (2022)Dual Distance Optimized Deep Quantization With Semantics-PreservingIEEE Signal Processing Letters10.1109/LSP.2022.316542629(1057-1061)Online publication date: 2022
    • (2022)Fast Adaptive Similarity Search through Variance-Aware Quantization2022 IEEE 38th International Conference on Data Engineering (ICDE)10.1109/ICDE53745.2022.00268(2969-2983)Online publication date: May-2022
    • (2021)Deep Multiple Length Hashing via Multi-task LearningProceedings of the 3rd ACM International Conference on Multimedia in Asia10.1145/3469877.3493591(1-5)Online publication date: 1-Dec-2021
    • (2021)Rank-Consistency Deep Hashing for Scalable Multi-Label Image SearchIEEE Transactions on Multimedia10.1109/TMM.2020.303453423(3943-3956)Online publication date: 2021
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