Results 191 to 200 of about 20,342 (243)
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DOUBLE HASHING WITH MULTIPLE PASSBITS
International Journal of Foundations of Computer Science, 2003We 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.
Martini, Paul M., Burkhard, Walter A.
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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.
Shengnan Wang, Chunguang Li
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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.
Shengnan Wang, Chunguang Li
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Computing in Science & Engineering, 2017
In the past few years, researchers have introduced several sorting algorithms to enhance time complexity, space complexity, and stability. A double hashing methodology first collects statistics about element distribution and then maps between elements of the array and indexes based on the knowledge collected during the first hashing.
Yasser M.K. Omar, Hoda Osama, Amr Badr
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In the past few years, researchers have introduced several sorting algorithms to enhance time complexity, space complexity, and stability. A double hashing methodology first collects statistics about element distribution and then maps between elements of the array and indexes based on the knowledge collected during the first hashing.
Yasser M.K. Omar, Hoda Osama, Amr Badr
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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.
Michael Mitzenmacher, Justin Thaler
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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
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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
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Double-Hashing Operation Mode for Encryption
2017 IEEE 7th Annual Computing and Communication Workshop and Conference (CCWC), 2017Block ciphers, hash-based encryption, and public-key ciphers are examples of data encryption techniques with different desired features. Strong block ciphers, like AES, must run in some mode of operation to encrypt data larger than the block size. Public-key ciphers, like RSA, are costly and usually used for key-sharing rather than encrypting the data ...
Sultan Almuhammadi, Ahmad Amro
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Double-Coding Density Sensitive Hashing
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.
Xiaoliang Tang +4 more
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Deep Double Center Hashing for Face Image Retrieval
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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Collision Resistant Double-Length Hashing
2010We give collision resistance bounds for blockcipher based, double-call, double-length hash functions using (k, n)-bit blockciphers with k > n. Ozen and Stam recently proposed a framework [21] for such hash functions that use 3n-to-2n-bit compression functions and two parallel calls to two independent blockciphers with 2n-bit key and n-bit block size.
Ewan Fleischmann +3 more
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An Efficient, Hybrid, Double-Hash StringMatching Algorithm
2019 IEEE Long Island Systems, Applications and Technology Conference (LISAT), 2019In this paper we show that combining some of the good features of the existing popular algorithms can be even more efficient. This new algorithm is hybrid as it employs features from Boyer-Moore-Horspool, Rabin-Karp and Raita algorithms. We compare the right most character as well as use two independent hash functions and no character by character ...
Mehmet Bicer, Xiaowen Zhang
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