Locality-sensitive hashing
The distortion of locality sensitive hashing
... objects, locality sensitive hashing (LSH) aims to construct a hash function family over the universe of objects such that the probability two objects hash to the same value is their ...
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Query-Adaptative Locality Sensitive Hashing
... hoc approaches have been proposed for vector quantization (see [3] for references), when finding the exact nearest neighbor is not ex- actly necessary, as long as the reconstruction error is limited. More specific ANN ...
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Research on Improved Locality Sensitive Hashing Algorithm
... important. Locality sensitive hashing algorithm is one of the most popular algorithms in similarity search, it is an approximate nearest neighbor algorithm that based on the establishment of ...
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Lattice-based locality sensitive hashing is optimal
... Locality sensitive hashing (LSH) was introduced by Indyk and Motwani (STOC ‘98) to give the first sublinear time algorithm for the c-approximate nearest neighbor (ANN) problem using only polynomial ...
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An Efficient Recommender System Using Locality Sensitive Hashing
... etc. Locality sensitive hashing is one of the state-of-the-art efficient algorithms that approximately preserving similarity but with significant dimension ...
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Bayesian locality sensitive hashing for fast similarity search
... of locality-sensitive hashing [12, 10], where the idea is to find a family of hash functions such that for a random hash function from this family, two objects with high similarity are very likely to ...
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Efficient Online Locality Sensitive Hashing via Reservoir Counting
... 4 Conclusion We have presented a novel approximation scheme we call Reservoir Counting, motivated here by a de- sire for greater space efficiency in Online Locality Sensitive Hashing. Going beyond ...
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Locality Sensitive Hashing for Set-Queries, Motivated by Group Recommendations
... 4 Alexandr Andoni and Ilya Razenshteyn. Tight lower bounds for data-dependent locality- sensitive hashing. In SOCG, pages 1–11. ACM, 2016. doi:10.4230/LIPIcs.SoCG.2016.9. 5 Liliana Ardissono, Anna ...
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Similarity join size estimation using locality sensitive hashing
... In this paper, we propose sampling based techniques that exploit the Locality Sensitive Hashing (LSH) scheme, which has been successfully applied in similarity searches across many domains. LSH ...
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Kernelized Locality-Sensitive Hashing for Fast Image Landmark Association
... This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. As the concept of war has evolved, navigation in urban environments where GPS may be degraded is ...
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Text and Content Based Image Retrieval Via Locality Sensitive Hashing
... of locality sensitive hashing which guarantees a sub-linear searching time on the visual ...the hashing, which further shortens the time spent on the visual ...
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Boosting multi-kernel Locality-Sensitive Hashing for scalable image retrieval
... 6. CONCLUSIONS This paper investigated a framework of Multi-Kernel Locality- Sensitive Hashing by exploring multiple kernels for efficient and scalable content-based image retrieval. We first ...
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Privacy-preserving distributed service recommendation based on locality-sensitive hashing
... However, traditional CF-based service recommendation approaches often assume that the historical user-service quality data is centralized, while neglect the distributed recommendation situation. Generally, distributed ...
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Sieving for shortest vectors in lattices using angular locality-sensitive hashing
... angular locality-sensitive hashing, we obtain Algorithm ...of locality-sensitive hashing are again spread out over the various iterations; at each iteration we only update the ...
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Locality sensitive hashing: a comparison of hash function types and querying mechanisms
... curse of dimensionality (B¨ohm et al., 2001; Beyer et al., 1999). This operation is required by many pattern recognition appli- cations. In image retrieval or object recognition, the numer- ous descriptors of an image ...
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Accelerating Large Scale Centroid-based Clustering with Locality Sensitive Hashing
... 1) Varying Number of Clusters: One of the most impor- tant parameters in validating how our algorithm scales is by exploring how it performs with datasets consisting of large numbers of clusters. As our algorithm is ...
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Multi-resolution sketches and locality sensitive hashing for fast trajectory processing
... develop Locality sensitive hashing (LSH) for this approximation problem, and it was subsequently improved upon in various works to obtain a query time sublinear in n, and polynomial dependence in d ...
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Clustering using Simhash and Locality Sensitive Hashing in Hadoop HDFS : An Infrastructure Extension
... Sree Chithra Thirunal College of Engineering, Thiruvnanthapuram, Kerala. [email protected], [email protected] Abstract— Apache’s Hadoop 1 , an open source implementation of Google’s Map/Reduce framework, is a ...
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Fast distributed video deduplication via locality-sensitive hashing with similarity ranking
... 6 Conclusions To achieve the fast deduplication of a large-scale video dataset, this paper proposed a distributed framework based on locality-sensitive hashing, which is generic and powerful to use ...
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Faster sieving for shortest lattice vectors using spherical locality-sensitive hashing
... is locality-sensitive hashing (LSH), introduced by Indyk and Motwani ...[21]. Locality-sensitive hash functions are functions h which map n-dimensional vectors w to low-dimensional ...
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