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Approximate K-Nearest Neighbor Search (AKNNS) has now become ubiquitous in modern applications, for example, as a fast search procedure with two tower deep learning models.
Two algorithms for constructing a delaunay triangulation
Der-Tsai Lee and Bruce J Schachter · 1980
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Extensions of lipschitz mappings into a hilbert space 26
William B Johnson and Joram Lindenstrauss · 1984
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Monotonic search networks for computer vision databases
DW Dearholt, N Gonzales, and G Kurup · 1988
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The r*-tree: An efficient and robust access method for points and rectangles
Norbert Beckmann, Hans-Peter Kriegel, Ralf Schneider, and Bernhard Seeger · 1990
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Voronoi diagrams—a survey of a fundamental geometric data structure
Franz Aurenhammer · 1991
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Approximate nearest neighbor queries in fixed dimensions
Sunil Arya and David M Mount · 1993
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Approximate nearest neighbors: towards removing the curse of dimensionality
Piotr Indyk and Rajeev Motwani · 1998
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Similarity search in high dimensions via hashing
Aristides Gionis, Piotr Indyk, Rajeev Motwani, et al · 1999
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Similarity estimation techniques from rounding algorithms
Moses S Charikar · 2002
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Pattern recognition
Christopher M Bishop · 2006
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Optimised kd-trees for fast image descriptor matching
Chanop Silpa-Anan and Richard Hartley · 2008
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Optimal quantization and bit allocation for compressing large discriminative feature space transforms
Etienne Marcheret, Vaibhava Goel, and Peder A Olsen · 2009
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Product quantization for nearest neighbor search
Herve Jegou, Matthijs Douze, and Cordelia Schmid · 2010
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Sequential projection learning for hashing with compact codes
Jun Wang, Sanjiv Kumar, and Shih-Fu Chang · 2010
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Efficient k-nearest neighbor graph construction for generic similarity measures
Wei Dong, Charikar Moses, and Kai Li · 2011
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Fast approximate nearest-neighbor search with k-nearest neighbor graph
Kiana Hajebi, Yasin Abbasi-Yadkori, Hossein Shahbazi, and Hong Zhang · 2011
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Optimized product quantization
Tiezheng Ge, Kaiming He, Qifa Ke, and Jian Sun · 2013
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K-means hashing: An affinity-preserving quantization method for learning binary compact codes
Kaiming He, Fang Wen, and Jian Sun · 2013
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Fast and accurate hashing via iterative nearest neighbors expansion
Zhongming Jin, Debing Zhang, Yao Hu, Shiding Lin, Deng Cai, and Xiaofei He · 2014
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Efanna: An extremely fast approximate nearest neighbor search algorithm based on knn graph
Cong Fu and Deng Cai · 2016
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Fanng: Fast approximate nearest neighbour graphs
Learning to screen for fast softmax inference on large vocabulary neural networks
Patrick H Chen, Si Si, Sanjiv Kumar, Yang Li, and Cho-Jui Hsieh · 2019
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Diskann: Fast accurate billion-point nearest neighbor search on a single node
Suhas Jayaram Subramanya, Fnu Devvrit, Harsha Vardhan Simhadri, Ravishankar Krishnawamy, and Rohan Kadekodi · 2019
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Billion-scale similarity search with gpus
Jeff Johnson, Matthijs Douze, and Hervé Jégou · 2019
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Random projections with asymmetric quantization
Xiaoyun Li and Ping Li · 2019
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Unsupervised neural quantization for compressed-domain similarity search
Stanislav Morozov and Artem Babenko · 2019
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Deep learning based recommender system: A survey and new perspectives
Shuai Zhang, Lina Yao, Aixin Sun, and Yi Tay · 2019
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Ben Harwood and Tom Drummond · 2016
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On approximately searching for similar word embeddings
Kohei Sugawara, Hayato Kobayashi, and Masajiro Iwasaki · 2016
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Fast approximate nearest neighbor search with the navigating spreading-out graph
Cong Fu, Chao Xiang, Changxu Wang, and Deng Cai · 2017
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Multiscale quantization for fast similarity search
Xiang Wu, Ruiqi Guo, Ananda Theertha Suresh, Sanjiv Kumar, Daniel N Holtmann-Rice, David Simcha, and Felix Yu · 2017
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Link and code: Fast indexing with graphs and compact regression codes
Matthijs Douze, Alexandre Sablayrolles, and Hervé Jégou · 2018
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Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs
Yu A Malkov and Dmitry A Yashunin · 2018
Cited alongside, same era.
Lsq++: Lower running time and higher recall in multi-codebook quantization
Julieta Martinez, Shobhit Zakhmi, Holger H Hoos, and James J Little · 2018
Cited alongside, same era.
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Ann-benchmarks: A benchmarking tool for approximate nearest neighbor algorithms
Martin Aumüller, Erik Bernhardsson, and Alexander Faithfull · 2020
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Accelerating large-scale inference with anisotropic vector quantization
Ruiqi Guo, Philip Sun, Erik Lindgren, Quan Geng, David Simcha, Felix Chern, and Sanjiv Kumar · 2020
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Improving approximate nearest neighbor search through learned adaptive early termination
Conglong Li, Minjia Zhang, David G Andersen, and Yuxiong He · 2020
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A note on graph-based nearest neighbor search
Hongya Wang, Zhizheng Wang, Wei Wang, Yingyuan Xiao, Zeng Zhao, and Kaixiang Yang · 2020
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Pecos: Prediction for enormous and correlated output spaces
Hsiang-Fu Yu, Kai Zhong, and Inderjit S Dhillon · 2020
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Spann: Highly-efficient billion-scale approximate nearest neighborhood search
Qi Chen, Bing Zhao, Haidong Wang, Mingqin Li, Chuanjie Liu, Zhiyong Zheng, Mao Yang, and Jingdong Wang · 2021
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An introduction to johnson-lindenstrauss transforms
Casper Benjamin Freksen · 2021
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High dimensional similarity search with satellite system graph: Efficiency, scalability, and unindexed query compatibility
Cong Fu, Changxu Wang, and Deng Cai · 2021
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