Learnable indexes and hashes



Dr. Wu-Jun LI’s excellent Lit review and practicalities supporting their own papers. Kevin Zakka’s kNN classification using Neighbourhood Components Analysis is an illustrated guide to a type of dimensionality reduction I had not heard of before that looks handy for nearest-neighbour search, which I suppose is the entry-level use here. (Dwibedi et al. 2019)

References

Beutel, Alex, Tim Kraska, H. Chi, Jeffrey Dean, and Neoklis Polyzotis. 2017. “A Machine Learning Approach to Databases Indexes.” In Advances In Neural Information Processing Systems. http://learningsys.org/nips17/assets/papers/paper_22.pdf.
Cao, Zhangjie, Mingsheng Long, Jianmin Wang, and Philip S. Yu. 2017. “HashNet: Deep Learning to Hash by Continuation.” arXiv:1702.00758 [cs], February. http://arxiv.org/abs/1702.00758.
Chiu, Chih-Yi, Amorntip Prayoonwong, and Yin-Chih Liao. 2020. “Learning to Index for Nearest Neighbor Search.” IEEE Transactions on Pattern Analysis and Machine Intelligence 42 (8): 1942–56. https://doi.org/10.1109/TPAMI.2019.2907086.
Dwibedi, Debidatta, Yusuf Aytar, Jonathan Tompson, Pierre Sermanet, and Andrew Zisserman. 2019. “Temporal Cycle-Consistency Learning,” April. https://arxiv.org/abs/1904.07846v1.
Gordo, Albert, Jon Almazan, Jerome Revaud, and Diane Larlus. 2016. “End-to-End Learning of Deep Visual Representations for Image Retrieval.” arXiv:1610.07940 [cs], October. http://arxiv.org/abs/1610.07940.
Graves, Alex, Greg Wayne, Malcolm Reynolds, Tim Harley, Ivo Danihelka, Agnieszka Grabska-Barwińska, Sergio Gómez Colmenarejo, et al. 2016. “Hybrid Computing Using a Neural Network with Dynamic External Memory.” Nature advance online publication (October). https://doi.org/10.1038/nature20101.
Kraska, Tim, Alex Beutel, Ed H. Chi, Jeffrey Dean, and Neoklis Polyzotis. 2017. “The Case for Learned Index Structures.” arXiv:1712.01208 [cs], December. http://arxiv.org/abs/1712.01208.
Lai, Hanjiang, Yan Pan, Ye Liu, and Shuicheng Yan. 2015. “Simultaneous Feature Learning and Hash Coding with Deep Neural Networks.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 3270–78. https://doi.org/10.1109/CVPR.2015.7298947.
Li, Wu-Jun, Sheng Wang, and Wang-Cheng Kang. 2015. “Feature Learning Based Deep Supervised Hashing with Pairwise Labels.” arXiv Preprint arXiv:1511.03855. https://cs.nju.edu.cn/lwj/paper/IJCAI16_DPSH.pdf.
Lin, Kevin, Huei-Fang Yang, Jen-Hao Hsiao, and Chu-Song Chen. 2015. “Deep Learning of Binary Hash Codes for Fast Image Retrieval.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 27–35. https://doi.org/10.1109/CVPRW.2015.7301269.
Liong, Erin, Jiwen Lu, Gang Wang, Pierre Moulin, and Jie Zhou. 2015. “Deep Hashing for Compact Binary Codes Learning.” In 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2475–83. https://doi.org/10.1109/CVPR.2015.7298862.
Mitra, Bhaskar, and Nick Craswell. 2017. “Neural Models for Information Retrieval.” arXiv:1705.01509 [cs], May. http://arxiv.org/abs/1705.01509.
Nagathan, Arvind, Jitendranath Mungara, and Manimozhi. 2014. “Content-Based Image Retrieval System Using Feed-Forward Backpropagation Neural Network.” International Journal of Computer Science and Network Security (IJCSNS) 14 (6): 70. http://paper.ijcsns.org/07_book/html/201406/201406013.html.
Schüle, Maximilian, Frédéric Simonis, Thomas Heyenbrock, Alfons Kemper, Stephan Günnemann, and Thomas Neumann. 2019. “In-Database Machine Learning: Gradient Descent andTensor Algebra for Main Memory Database Systems.” https://doi.org/10.18420/BTW2019-16.
Wang, J., T. Zhang, j song, N. Sebe, and H. T. Shen. 2018. “A Survey on Learning to Hash.” IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (4): 769–90. https://doi.org/10.1109/TPAMI.2017.2699960.
Xia, Rongkai, Yan Pan, Hanjiang Lai, Cong Liu, and Shuicheng Yan. 2014. “Supervised Hashing for Image Retrieval via Image Representation Learning.” In AAAI, 1:2156–62.
Xu, Jiaming, Peng Wang, Guanhua Tian, Bo Xu, Jun Zhao, Fangyuan Wang, and Hongwei Hao. 2015. “Convolutional Neural Networks for Text Hashing.” In IJCAI, 1369–75. http://www.ijcai.org/Proceedings/15/Papers/197.pdf.
Yang, H. F., K. Lin, and C. S. Chen. 2018. “Supervised Learning of Semantics-Preserving Hash via Deep Convolutional Neural Networks.” IEEE Transactions on Pattern Analysis and Machine Intelligence 40 (2): 437–51. https://doi.org/10.1109/TPAMI.2017.2666812.
Zhang, Ruimao, Liang Lin, Rui Zhang, Wangmeng Zuo, and Lei Zhang. 2015. “Bit-Scalable Deep Hashing with Regularized Similarity Learning for Image Retrieval and Person Re-Identification.” IEEE Transactions on Image Processing 24 (12): 4766–79.
Zoran, Daniel, Balaji Lakshminarayanan, and Charles Blundell. 2017. “Learning Deep Nearest Neighbor Representations Using Differentiable Boundary Trees.” arXiv:1702.08833 [cs], February. http://arxiv.org/abs/1702.08833.

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