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A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search
Mengzhao Wang, Xiaoliang Xu, Qiang Yue, and Yuxiang Wang. 2021 · 1978
Earlier work this paper cites.
Approximate nearest neighbor queries in fixed dimensions. In Proceedings of the fourth annual ACM-SIAM symposium on Discrete algorithms , Vol. 93. 271–280
Sunil Arya and David M Mount. 1993 · 1993
Earlier work this paper cites.
Approximate nearest neighbors: towards removing the curse of dimensionality. In Proceedings of the thirtieth annual ACM symposium on Theory of computing . 604–613
Piotr Indyk and Rajeev Motwani. 1998 · 1998
Earlier work this paper cites.
Virtual memory: issues of implementation
Bruce Jacob and Trevor Mudge. 1998 · 1998
Earlier work this paper cites.
Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform. In Proceedings of the thirty-eighth annual ACM symposium on Theory of computing . 557–563
Nir Ailon and Bernard Chazelle. 2006 · 2006
Earlier work this paper cites.
Fast nearest neighbor retrieval for bregman divergences. In Proceedings of the 25th international conference on Machine learning - ICML ’08 . ACM Press, Helsinki, Finland, 112–119
Lawrence Cayton. 2008 · 2008
Earlier work this paper cites.
Optimised KD-trees for fast image descriptor matching. In 2008 IEEE Conference on Computer Vision and Pattern Recognition . IEEE, Anchorage, AK, USA, 1–8
Chanop Silpa-Anan and Richard Hartley. 2008 · 2008
Earlier work this paper cites.
Product Quantization for Nearest Neighbor Search
Herve Jégou, Matthijs Douze, and Cordelia Schmid. 2011 · 2010
Earlier work this paper cites.
A similarity measure for indefinite rankings
William Webber, Alistair Moffat, and Justin Zobel. 2010 · 2010
Earlier work this paper cites.
Optimized product quantization
Tiezheng Ge, Kaiming He, Qifa Ke, and Jian Sun. 2013 · 2013
Earlier work this paper cites.
Additive Quantization for Extreme Vector Compression. In 2014 IEEE Conference on Computer Vision and Pattern Recognition . IEEE, Columbus, OH, USA, 931–938
Artem Babenko and Victor Lempitsky. 2014 · 2014
Earlier work this paper cites.
Scalable Nearest Neighbor Algorithms for High Dimensional Data
Marius Muja and David G. Lowe. 2014 · 2014
Earlier work this paper cites.
GloVe: Global Vectors for Word Representation. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) . 1532–1543
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
Earlier work this paper cites.
Composite quantization for approximate nearest neighbor search. In International Conference on Machine Learning . PMLR, 838–846
Ting Zhang, Chao Du, and Jingdong Wang. 2014 · 2014
Earlier work this paper cites.
Cache locality is not enough: high-performance nearest neighbor search with product quantization fast scan
Fabien André, Anne-Marie Kermarrec, and Nicolas Le Scouarnec. 2015 · 2015
Earlier work this paper cites.
Scalable semantic matching of queries to ads in sponsored search advertising. In Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval . 375–384
Mihajlo Grbovic, Nemanja Djuric, Vladan Radosavljevic, Fabrizio Silvestri, Ricardo Baeza-Yates, Andrew Feng, Erik Ordentlich, Lee Yang, and Gavin Owens. 2016 · 2016
Earlier work this paper cites.
A Survey on Learning to Hash
Jingdong Wang, Ting Zhang, Jingkuan Song, Nicu Sebe, and Heng Tao Shen. 2018 · 2017
Earlier work this paper cites.
Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs
Yu A Malkov and Dmitry A Yashunin. 2018 · 2018
Earlier work this paper cites.
[Invited Paper] A Survey of Product Quantization
Yusuke Matsui, Yusuke Uchida, Herve Jegou, and Shin’ichi Satoh. 2018 · 2018
Earlier work this paper cites.
Quicker ADC : Unlocking the Hidden Potential of Product Quantization With SIMD
Fabien Andre, Anne-Marie Kermarrec, and Nicolas Le Scouarnec. 2021 · 2019
Earlier work this paper cites.
ANN-Benchmarks: A benchmarking tool for approximate nearest neighbor algorithms
Martin Aumüller, Erik Bernhardsson, and Alexander Faithfull. 2020a · 2019
Cited alongside, same era.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT . 4171–4186
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Fast approximate nearest neighbor search with the navigating spreading-out graph
Cong Fu, Chao Xiang, Changxu Wang, and Deng Cai. 2019 · 2019
Cited alongside, same era.
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 · 2019
Cited alongside, same era.
Billion-scale similarity search with GPUs
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 2019 · 2019
Learning transferable visual models from natural language supervision. In International conference on machine learning . PMLR, 8748–8763
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Later among the works it cites.
Trident: Harnessing Architectural Resources for All Page Sizes in X86 Processors. In MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture (Virtual Event, Greece) (MICRO ’21) . Association for Computing Machinery, New York, NY, USA, 1106–1120
Venkat Sri Sai Ram, Ashish Panwar, and Arkaprava Basu. 2021 · 2021
Later among the works it cites.
Results of the NeurIPS’21 Challenge on Billion-Scale Approximate Nearest Neighbor Search. https://big-ann-benchmarks.com/ . In NeurIPS 2021 Competitions and Demonstrations Track . PMLR, 177–189
Harsha Vardhan Simhadri, George Williams, Martin Aumüller, Matthijs Douze, Artem Babenko, Dmitry Baranchuk, Qi Chen, Lucas Hosseini, Ravishankar Krishnaswamny, Gopal Srinivasa, et al · 2021
Later among the works it cites.
Intel® Memory Latency Checker
Vish Viswanathan, Karthik Kumar, Thomas Willhalm, and Sri Sakthivelu. 2013 · 2021
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Cited alongside, same era.
Billion-Scale Similarity Search with GPUs
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 2021 · 2019
Cited alongside, same era.
Approximate Nearest Neighbor Search on High Dimensional Data — Experiments, Analyses, and Improvement
Wen Li, Ying Zhang, Yifang Sun, Wei Wang, Mingjie Li, Wenjie Zhang, and Xuemin Lin. 2020 · 2019
Cited alongside, same era.
Performance of Gather/Scatter Operations
Douglas Michael Pase and Anthony Michael Agelastos. 2019 · 2019
Cited alongside, same era.
Accelerating large-scale inference with anisotropic vector quantization. In International Conference on Machine Learning . PMLR, 3887–3896
Ruiqi Guo, Philip Sun, Erik Lindgren, Quan Geng, David Simcha, Felix Chern, and Sanjiv Kumar. 2020 · 2020
Cited alongside, same era.
Dense Passage Retrieval for Open-Domain Question Answering. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) . 6769–6781
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
Cited alongside, same era.
Lightrec: A memory and search-efficient recommender system. In Proceedings of The Web Conference 2020 . 695–705
Defu Lian, Haoyu Wang, Zheng Liu, Jianxun Lian, Enhong Chen, and Xing Xie. 2020 · 2020
Cited alongside, same era.
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
Cited alongside, same era.
Later among the works it cites.
Retrieval-augmented diffusion models
Andreas Blattmann, Robin Rombach, Kaan Oktay, Jonas Müller, and Björn Ommer. 2022 · 2022
Later among the works it cites.
Improving language models by retrieving from trillions of tokens. In Proceedings of the 39th International Conference on Machine Learning . PMLR, 2206–2240
Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George Bm Van Den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, et al · 2022
Later among the works it cites.
Competition-level code generation with alphacode
Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, et al · 2022
Later among the works it cites.
Speed-ANN: Low-Latency and High-Accuracy Nearest Neighbor Search via Intra-Query Parallelism
Zhen Peng, Minjia Zhang, Kai Li, Ruoming Jin, and Bin Ren. 2022 · 2022
Later among the works it cites.
Everything at once-multi-modal fusion transformer for video retrieval. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 20020–20029
Nina Shvetsova, Brian Chen, Andrew Rouditchenko, Samuel Thomas, Brian Kingsbury, Rogerio S Feris, David Harwath, James Glass, and Hilde Kuehne. 2022 · 2022
Later among the works it cites.
Residual Vector Product Quantization for Approximate Nearest Neighbor Search. In Advances in Knowledge Discovery and Data Mining: 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16–19, 2022, Proceedings, Part I . Springer, 208–220
Zhi Xu, Lushuai Niu, Ruimin Meng, Longyang Zhao, and Jianqiu Ji. 2022 · 2022
Later among the works it cites.
Connecting Compression Spaces with Transformer for Approximate Nearest Neighbor Search. In Computer Vision – ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XIV . Springer Nature Switzerland, 515–530
Haokui Zhang, Buzhou Tang, Wenze Hu, and Xiaoyu Wang. 2022 · 2022
Later among the works it cites.
Similarity search in the blink of an eye with compressed indices
Cecilia Aguerrebere, Ishwar Bhati, Mark Hildebrand, Mariano Tepper, and Ted Willke. 2023 · 2023
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Benchmarking nearest neighbors
Martin Aumüller, Erik Bernhardsson, and Alexander Faithfull. 2020b · 2023
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Benchmarks for Billion-Scale Similarity Search
Artem Babenko and Victor Lempitsky. 2021 · 2023
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Deep billion-scale indexing
Artem Babenko and Victor Lempitsky. 22016 · 2023
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SPTAG: A library for fast approximate nearest neighbor search
Qi Chen, Haidong Wang, Mingqin Li, Gang Ren, Scarlett Li, Jeffery Zhu, Jason Li, Chuanjie Liu, Lintao Zhang, and Jingdong Wang. 2018 · 2023
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IEEE Standard for Binary Floating-Point Arithmetic
IEEE. 1985 · 2023
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Nearest Neighbor Search with Neighborhood Graph and Tree for High-dimensional Data
Masajiro Iwasaki and Daisuke Miyazaki. 2018a · 2023
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Datasets for approximate nearest neighbor search
Herve Jegou, Matthijs Douze, and Cordelia Schmid. 2010 · 2023
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