Results 201 to 210 of about 2,148,635 (268)
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Remainder Quotient Double Hashing Technique in Closed Hashing Search Process
SSRN Electronic Journal, 2019Searching is one of the most important process in many activities to access the data or elements. It can be done both in online and offline mode. Many algorithms are used in data structure to perform search process. Hash search algorithm is one of them which are independent of the number of elements inserted into the table.
Stuti Pandey, Abhay Kumar Agarwal
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IEEE Transactions on Big Data, 2019
Hashing has been widely used for nearest neighbors search over big data. Hashing encodes high dimensional data points into binary codes. Most hashing methods use the single-bit quantization (SBQ) strategy for coding the data. However, this strategy often encodes neighboring points into totally different bits.
Chunguang Li, Shengnan Wang
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Hashing has been widely used for nearest neighbors search over big data. Hashing encodes high dimensional data points into binary codes. Most hashing methods use the single-bit quantization (SBQ) strategy for coding the data. However, this strategy often encodes neighboring points into totally different bits.
Chunguang Li, Shengnan Wang
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Peeling arguments and double hashing
2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2012The analysis of several algorithms and data structures can be reduced to the analysis of the following greedy “peeling” process: start with a random hypergraph; find a vertex of degree at most k, and remove it and all of its adjacent hyperedges from the graph; repeat until there is no suitable vertex.
Justin Thaler, Michael Mitzenmacher
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On the Prerequisite of Coprimes in Double Hashing
2019Hashing is a widely used technique for performing dictionary operations. Even though it is selected from the problem of collision, alternative hashing technique, open addressing has been developed. One such open addressing scheme, double hashing uses two hash functions to perform the search.
Vivek Kumar
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Deep Double Center Hashing for Face Image Retrieval
Chinese Conference on Pattern Recognition and Computer Vision, 2021Hashing is an effective and widely used technology for fast approximate nearest neighbor search in large-scale images. In recent years, it has been combined with a powerful feature learning model, convolutional neural network(CNN), to boost the efficiency of large-scale image retrieval. In this paper, we introduce a new Deep Double Center Hashing (DDCH)
Xin Fu, Wenzhong Wang, Jin Tang
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DOUBLE HASHING WITH MULTIPLE PASSBITS
International Journal of Foundations of Computer Science, 2003 We present a novel extension to passbits providing significant reduction to unsuccessful search lengths for open addressing collision resolution hashing. Both the experimental and analytical results presented demonstrate the dramatic reductions possible.
Paul M. Martini, Walter A. Burkhard
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Double-Coding Density Sensitive Hashing
International Conference on Neural Information Processing, 2017This paper proposes a double-coding density sensitive hashing (DCDSH) method. DCDSH accomplishes approximate nearest neighbor (ANN) search tasks based on its double coding scheme. First, DCDSH generates real-valued hash codes by projecting objects along the principle hyper-planes.
Xiangfu Meng +4 more
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Journal of the American Society for Information Science, 1972 AbstractThis paper generalizes the direct‐chaining technique of hash coding in a manner that is useful for storing records on the basis of non‐unique search keys. Such a capability is of particular interest for library automation and information retrieval. Two hash functions are used instead of one, and to take advantage of the information contained in
Abraham Bookstein
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Density-Based Clustering by Double-Bit Quantization Hashing
Communications in Computer and Information Science, 2019Grouping data into the different parts, while the objects in the same part have the most similarity with each other and cannot belong to the other parts, called data clustering. Clustering used for data analysis in data mining, so far, many different algorithms for clustering have been offered.
Mahdieh Dehghani +2 more
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Deep Learning-Based Image Retrieval With Unsupervised Double Bit Hashing
IEEE transactions on circuits and systems for video technology (Print), 2023Unsupervised image hashing is a widely used technique for large-scale image retrieval. This technique maps an image to a finite length of binary codes without extensive human-annotated data for compact storage and effective semantic retrieval. This study
Jing-Ming Guo +3 more
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