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State-of-the-art algorithms for Approximate Nearest Neighbor Search (ANNS) such as DiskANN, FAISS-IVF, and HNSW build data dependent indices that offer substantially better accuracy and search efficiency over data-agnostic indices by overfitting to the index data distribution.
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.
Similarity Search in High Dimensions via Hashing. In Proceedings of the 25th International Conference on Very Large Data Bases (VLDB ’99) . Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 518–529
Aristides Gionis, Piotr Indyk, and Rajeev Motwani. 1999 · 1999
Earlier work this paper cites.
Fundamentals of content-based image retrieval
Fuhui Long, Hongjiang Zhang, and David Dagan Feng. 2003 · 2003
Earlier work this paper cites.
Model-Based Robust Deep Learning: Generalizing to Natural, Out-of-Distribution Data
Alexander Robey, Hamed Hassani, and George J. Pappas. 2020 · 2005
Earlier work this paper cites.
Dimensionality Reduction by Learning an Invariant Mapping. In 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’06) , Vol. 2. 1735–1742
R. Hadsell, S. Chopra, and Y. LeCun. 2006 · 2006
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.
Optimized Product Quantization for Approximate Nearest Neighbor Search. In 2013 IEEE Conference on Computer Vision and Pattern Recognition . 2946–2953
Tiezheng Ge, Kaiming He, Qifa Ke, and Jian Sun. 2013 · 2013
Earlier work this paper cites.
Learning Deep Structured Semantic Models for Web Search Using Clickthrough Data. In Proceedings of the 22nd ACM International Conference on Information & Knowledge Management (San Francisco, California, USA) (CIKM ’13) . Association for Computing Machinery, New York, NY, USA, 2333–2338
Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, and Larry Heck. 2013 · 2013
Earlier work this paper cites.
Efficient approximate nearest neighbor search by optimized residual vector quantization. In 2014 12th International Workshop on Content-Based Multimedia Indexing (CBMI) . 1–4
Liefu Ai, Junqing Yu, Tao Guan, and Yunfeng He. 2014 · 2014
Earlier work this paper cites.
Additive Quantization for Extreme Vector Compression. In 2014 IEEE Conference on Computer Vision and Pattern Recognition . 931–938
Artem Babenko and Victor Lempitsky. 2014 · 2014
Earlier work this paper cites.
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks. In Advances in Neural Information Processing Systems , Z. Ghahramani, M. Welling, C. Cortes, N. Lawrence, and K.Q. Weinberger (Eds.), Vol. 27. Curran Associates, Inc
Alexey Dosovitskiy, Jost Tobias Springenberg, Martin Riedmiller, and Thomas Brox. 2014 · 2014
Earlier work this paper cites.
Locally Optimized Product Quantization for Approximate Nearest Neighbor Search. In 2014 IEEE Conference on Computer Vision and Pattern Recognition . 2329–2336
Yannis Kalantidis and Yannis Avrithis. 2014 · 2014
Earlier work this paper cites.
A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval. In Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management (Shanghai, China) (CIKM ’14) . Association for Computing Machinery, New York, NY, USA, 101–110
Yelong Shen, Xiaodong He, Jianfeng Gao, Li Deng, and Grégoire Mesnil. 2014 · 2014
Earlier work this paper cites.
Deep learning for content-based image retrieval: A comprehensive study. In Proceedings of the 22nd ACM international conference on Multimedia . 157–166
Ji Wan, Dayong Wang, Steven Chu Hong Hoi, Pengcheng Wu, Jianke Zhu, Yongdong Zhang, and Jintao Li. 2014 · 2014
Earlier work this paper cites.
Composite Quantization for Approximate Nearest Neighbor Search. In Proceedings of the 31st International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 32) , Eric P. Xing and Tony Jebara (Eds.). PMLR, Bejing, China, 838–846
Ting Zhang, Chao Du, and Jingdong Wang. 2014 · 2014
Earlier work this paper cites.
Practical and Optimal LSH for Angular Distance. In Advances in Neural Information Processing Systems , C. Cortes, N. Lawrence, D. Lee, M. Sugiyama, and R. Garnett (Eds.), Vol. 28. Curran Associates, Inc
Alexandr Andoni, Piotr Indyk, Thijs Laarhoven, Ilya Razenshteyn, and Ludwig Schmidt. 2015 · 2015
Earlier work this paper cites.
TensorFlow: A system for large-scale machine learning. In 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16) . 265–283
Martin Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek G. Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng. 2016 · 2016
Earlier work this paper cites.
The extreme classification repository: Multi-label datasets and code
K. Bhatia, K. Dahiya, H. Jain, P. Kar, A. Mittal, Y. Prabhu, and M. Varma. 2016 · 2016
Cited alongside, same era.
Revisiting Additive Quantization. In ECCV (2) . 137–153
Julieta Martinez, Joris Clement, Holger H. Hoos, and James J. Little. 2016 · 2016
Cited alongside, same era.
Speedup Graph Processing by Graph Ordering. In Proceedings of the 2016 International Conference on Management of Data (San Francisco, California, USA) (SIGMOD ’16) . Association for Computing Machinery, New York, NY, USA, 1813–1828
Hao Wei, Jeffrey Xu Yu, Can Lu, and Xuemin Lin. 2016 · 2016
Cited alongside, same era.
Squeeze-and-Excitation Networks
Jie Hu, Li Shen, Samuel Albanie, Gang Sun, and Enhua Wu. 2017 · 2017
Cited alongside, same era.
Revisiting the Inverted Indices for Billion-Scale Approximate Nearest Neighbors. In Proceedings of the European Conference on Computer Vision (ECCV)
Dmitry Baranchuk, Artem Babenko, and Yury Malkov. 2018 · 2018
Dense Passage Retrieval for Open-Domain Question Answering. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) . Association for Computational Linguistics, Online, 6769–6781
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
Later among the works it cites.
Turing Bletchley: A Universal Image Language Representation model by Microsoft
Facebook AI. 2021 · 2021
Later among the works it cites.
Deep Random Projection Outlyingness for Unsupervised Anomaly Detection
Martin Bauw, Santiago Velasco-Forero, Jesus Angulo, Claude Adnet, and Olivier Airiau. 2021 · 2021
Later among the works it cites.
Graph Reordering for Cache-Efficient Near Neighbor Search
Benjamin Coleman, Santiago Segarra, Anshumali Shrivastava, and Alex Smola. 2021 · 2021
Later among the works it cites.
Provably Robust Detection of Out-of-distribution Data (almost) for free
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Cited alongside, same era.
Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs
Yu A. Malkov and D. A. Yashunin. 2020 · 2018
Cited alongside, same era.
LSQ++: Lower running time and higher recall in multi-codebook quantization. In Proceedings of the European Conference on Computer Vision (ECCV)
Julieta Martinez, Shobhit Zakhmi, Holger H. Hoos, and James J. Little. 2018 · 2018
Cited alongside, same era.
Representation Learning with Contrastive Predictive Coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals. 2018 · 2018
Cited alongside, same era.
ANN-Benchmarks: A Benchmarking Tool for Approximate Nearest Neighbor Algorithms
Martin Aumüller, Erik Bernhardsson, and Alexander Faithfull. 2020 · 2019
Cited alongside, same era.
Learning Representations by Maximizing Mutual Information Across Views. In Advances in Neural Information Processing Systems , H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, and R. Garnett (Eds.), Vol. 32. Curran Associates, Inc
Philip Bachman, R Devon Hjelm, and William Buchwalter. 2019 · 2019
Cited alongside, same era.
Overview of the TREC 2019 deep learning track. In Text REtrieval Conference (TREC) . TREC
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M. Voorhees. 2020 · 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.
Alexander Meinke, Julian Bitterwolf, and Matthias Hein. 2021 · 2021
Later among the works it cites.
Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization. In Proceedings of the 38th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 139) , Marina Meila and Tong Zhang (Eds.). PMLR, 7721–7735
John P Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, and Ludwig Schmidt. 2021 · 2021
Later among the works it cites.
Learning Transferable Visual Models From Natural Language Supervision. In Proceedings of the 38th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 139) , Marina Meila and Tong Zhang (Eds.). PMLR, 8748–8763
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. 2021 · 2021
Later among the works it cites.
PnPOOD : Out-Of-Distribution Detection for Text Classification via Plug andPlay Data Augmentation
Mrinal Rawat, Ramya Hebbalaguppe, and Lovekesh Vig. 2021 · 2021
Later among the works it cites.
Text-to-Image-1B: Benchmarks for Billion-Scale Similarity Search
Yandex Research. 2021 · 2021
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Turing Bletchley: A Universal Image Language Representation model by Microsoft
Saurabh Tiwary. 2021 · 2021
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Do We Really Need to Learn Representations from In-domain Data for Outlier Detection?
Zhisheng Xiao, Qing Yan, and Yali Amit. 2021 · 2021
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Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval. In International Conference on Learning Representations (ICLR)
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, and Arnold Overwijk. 2021 · 2021
Later among the works it cites.
Similarity Search: ScaNN and 4-bit PQ
Takuma Yamaguchi. 2021 · 2021
Later among the works it cites.
Nearest Neighbor Search with Compact Codes: A Decoder Perspective. In Proceedings of the 2022 International Conference on Multimedia Retrieval (Newark, NJ, USA) (ICMR ’22) . Association for Computing Machinery, New York, NY, USA, 167–175
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Harsha Vardhan Simhadri, George Williams, Martin Aumüller, Matthijs Douze, Artem Babenko, Dmitry Baranchuk, Qi Chen, Lucas Hosseini, Ravishankar Krishnaswamy, Gopal Srinivasa, Suhas Jayaram Subramanya, and Jingdong Wang. 2022 · 2022
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