Hashing


Random Hashing
  • Alexandr Andoni, Ilya Razenshteyn, Negev Shekel Nosatzki.  LSH forest: Practical algorithms made theoretical.  ACM-SIAM Symposium on Discrete Algorithms, 2017 [paper] [bibtex]
  • Alexandr Andoni, Ilya Razenshteyn.  Tight lower bounds for data-dependent locality-sensitive hashing.  arXiv, 2015 [paper] [bibtex]
  • Alexandr Andoni, Piotr Indyk, Thijs Laarhoven, Ilya Razenshteyn, Ludwig Schmidt.  Practical and optimal LSH for angular distance.  Neural Information Processing Systems, 2015 [paper] [bibtex]
  • Alexandr Andoni, Piotr Indyk, Huy L Nguyen, Ilya Razenshteyn.  Beyond locality-sensitive hashing.  ACM-SIAM Symposium on Discrete Algorithms, 2014 [paper] [bibtex]
  • A Shrivastava, P Li .  Asymmetric LSH (ALSH) for sublinear time maximum inner product search (MIPS).  Neural Information Processing Systems, 2014 [paper] [bibtex]
  • Alexandr Andoni.  Nearest Neighbor Search: the Old, the New, and the Impossible.  Massachusetts Institute of Technology, 2009 [paper] [bibtex]
  • Alexandr Andoni, Piotr Indyk, Robert Krauthgamer, Huy L Nguyen.  Approximate line nearest neighbor in high dimensions.  ACM-SIAM Symposium on Discrete Algorithms, 2009 [paper] [bibtex]
  • Gregory Shakhnarovich, Trevor Darrell, Piotr Indyk.  Nearest-neighbor methods in learning and vision.  IEEE Trans. Neural Networks, 2008 [paper] [bibtex]
  • Alexandr Andoni, Dorian Croitoru, Mihai Patrascu.  Hardness of nearest neighbor under L-infinity.  Foundations of Computer Science, 2008 [paper] [bibtex]
  • Piotr Indyk, Assaf Naor.  Nearest-neighbor-preserving embeddings.  ACM Transactions on Algorithms, 2007 [paper] [bibtex]
  • Alexandr Andoni, Piotr Indyk.  Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions.  Foundations of Computer Science, 2006 [paper] [bibtex]
  • Piotr Indyk.  Near optimal hashing algorithms for approximate near (est) neighbor problem.  Workshop on Algorithms for Modern Massive Data Sets, 2006 [paper] [bibtex]
  • Alexandr Andoni, Piotr Indyk.  Efficient algorithms for substring near neighbor problem.  ACM-SIAM Symposium on Discrete Algorithms, 2006 [paper] [bibtex]
  • Alexandr Andoni, Piotr Indyk.  New LSH-based algorithm for approximate nearest neighbor.  Massachusetts Institute of Technology, 2005 [paper] [bibtex]
  • Alexandr Andoni.  Approximate nearest neighbor problem in high dimensions.  Massachusetts Institute of Technology, 2005 [paper] [bibtex]
  • Piotr Indyk.  Approximate nearest neighbor under edit distance via product metrics.  Symposium on Computational Geometry, 2004 [paper] [bibtex]
  • Mayur Datar, Nicole Immorlica, Piotr Indyk, Vahab S Mirrokni.  Locality-sensitive hashing scheme based on p-stable distributions.  Symposium on Computational Geometry, 2004 [paper] [bibtex]
  • Piotr Indyk.  Approximate nearest neighbor algorithms for Fréchet distance via product metrics.  Symposium on Computational Geometry, 2002 [paper] [bibtex]

Unsupervised Hashing
  • Fumin Shen, Yan Xu, Li Liu, Yang Yang, Zi Huang, Heng Tao Shen.  Unsupervised Deep Hashing with Similarity-Adaptive and Discrete Optimization.  IEEE Transactions on Pattern Analysis and Machine Intelligence, 2018 [paper] [bibtex]
  • Yuchen Guo, Guiguang Ding, Li Liu, Jungong Han, Ling Shao.  Learning to hash with optimized anchor embedding for scalable retrieval.  IEEE Transactions on Image Processing, 2017 [paper] [bibtex]
  • Qinghao Hu, Jiaxiang Wu, Jian Cheng, Lifang Wu, Hanqing Lu.  Pseudo Label based Unsupervised Deep Discriminative Hashing for Image Retrieval.  ACM Conference on Multimedia, 2017 [paper] [bibtex]
  • Qi Dai, Jianguo Li, Jingdong Wang, Yu-Gang Jiang.  Binary Optimized Hashing.  ACM Multimedia Conference, 2016 [paper] [bibtex]
  • Xianglong Liu, Yadong Mu, Danchen Zhang, Bo Lang, Xuelong Li.  Large-scale unsupervised hashing with shared structure learning.  IEEE transactions on cybernetics, 2015 [paper] [code] [bibtex]
  • Yan Xia, Kaiming He, Pushmeet Kohli, Jian Sun.  Sparse Projections for High-Dimensional Binary Codes.  IEEE Conference on Computer Vision and Pattern Recognition, 2015 [paper] [bibtex]
  • Tiezheng Ge, Kaiming He, Jian Sun.  Product Sparse Coding.  IEEE Conference on Computer Vision and Pattern Recognition, 2014 [paper] [bibtex]
  • Kaiming He, Fang Wen, Jian Sun.  K-means hashing: An affinity-preserving quantization method for learning binary compact codes.  IEEE Conference on Computer Vision and Pattern Recognition, 2013 [paper] [bibtex]
  • Yunchao Gong, Svetlana Lazebnik.  Iterative quantization: A procrustean approach to learning binary codes.  IEEE Conference on Computer Vision and Pattern Recognition, 2011 [paper] [bibtex]
  • Wei Liu, Jun Wang, Sanjiv Kumar, Shih-Fu Chang.  Hashing with Graphs.  International Conference on Machine Learning, 2011 [paper] [bibtex]
  • Mohammad Norouzi, David J Fleet.  Minimal Loss Hashing for Compact Binary Codes.  International Conference on Machine Learning, 2011 [paper] [bibtex]

Supervised Hashing
  • Jingkuan Song, Hanwang Zhang, Xiangpeng Li, Lianli Gao, Meng Wang, Richang Hong.  Self-Supervised Video Hashing with Hierarchical Binary Auto-encoder.  ARXIV, 2018 [paper] [bibtex]
  • Chao Ma, Ivor W Tsang, Fumin Shen, Chuancai Liu.  Error Correcting Input and Output Hashing.  TOC(Transactions on Cybernetics), 2018 [paper] [bibtex]
  • Xiaopeng Zhang, Hui Zhang, Yong Chen, Xianglong Liu.  Large-Margin Supervised Hashing.  International Conference on Neural Information Processing, 2017 [paper] [bibtex]
  • Zhixiang Chen, Jiwen Lu, Jianjiang Feng, Jie Zhou.  Nonlinear discrete hashing.  ACM Conference on Multimedia, 2017 [paper] [bibtex]
  • Zhixiang Chen, Jiwen Lu, Jianjiang Feng, Jie Zhou.  Nonlinear Sparse Hashing.  ACM Conference on Multimedia, 2017 [paper] [bibtex]
  • Jingkuan Song, Tao He, Hangbo Fan, Lianli Gao.  Deep Discrete Hashing with Self-supervised Pairwise Labels.  Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2017 [paper] [bibtex]
  • Qing-Yuan Jiang, Wu-Jun Li.  Asymmetric Deep Supervised Hashing.  arXiv, 2017 [paper] [bibtex]
  • Anshumali Shrivastava.  Optimal densification for fast and accurate minwise hashing.  arXiv, 2017 [paper] [bibtex]
  • Liangfu Cao, Lianli Gao, Jingkuan Song, Fumin Shen, Yuan Wang.  Multiple hierarchical deep hashing for large scale image retrieval.  Multimedia Tools and Applications, 2017 [paper] [bibtex]
  • Sixiu Chen, Fumin Shen, Yang Yang, Xing Xu, Jingkuan Song.  Supervised hashing with adaptive discrete optimization for multimedia retrieval.  Neurocomputing, 2017 [paper] [bibtex]
  • Xin Yuan, Jiwen Lu, Zhixiang Chen, Jianjiang Feng, Jie Zhou.  Reconstruction-based supervised hashing.  IEEE International Conference on Multimedia and Expo, 2017 [paper] [bibtex]
  • Yuchen Guo, Xin Zhao, Guiguang Ding, Jungong Han.  On Trivial Solution and High Correlation Problems in Deep Supervised Hashing.  AAAI Conference on Artificial Intelligence, 2018 [paper] [bibtex]
  • Shiyuan He, Guo Ye, Mengqiu Hu, Yang Yang, Fumin Shen, Heng Tao Shen, Xuelong Li.  Learning binary codes with local and inner data structure.  Neurocomputing, 2017 [paper] [bibtex]
  • Han Zhu, Mingsheng Long, Jianmin Wang, Yue Cao.  Deep Hashing Network for Efficient Similarity Retrieval.  AAAI Conference on Artificial Intelligence, 2016 [paper][code] [bibtex]
  • Jingkuan Song, Lianli Gao, Fuhao Zou, Yan Yan, Nicu Sebe.  Deep and fast: Deep learning hashing with semi-supervised graph construction.  Image and Vision Computing, 2016 [paper] [bibtex]
  • Yang Yang, Yadan Luo, Weilun Chen, Fumin Shen, Jie Shao, Heng Tao Shen.  Zero-shot hashing via transferring supervised knowledge.  ACM Multimedia Conference, 2016 [paper] [bibtex]
  • Zijia Lin, Guiguang Ding, Jungong Han, Jianmin Wang.  Cross-view Retrieval via Supervised Semantics-Preserving Hashing.  IEEE Transactions on Cybernetics, 2016 [paper] [bibtex]
  • Wang-Cheng Kang, Wu-Jun Li, Zhi-Hua Zhou.  Column Sampling Based Discrete Supervised Hashing.  AAAI Conference on Artificial Intelligence, 2016 [paper] [bibtex]
  • Haomiao Liu, Ruiping Wang, Shiguang Shan, Xilin Chen.  Deep supervised hashing for fast image retrieval.  IEEE Conference on Computer Vision and Pattern Recognition, 2016 [paper] [bibtex]
  • Yue Cao, Mingsheng Long, Jianmin Wang, Han Zhu, Qingfu Wen.  Deep quantization network for efficient image retrieval.  AAAI Conference on Artificial Intelligence, 2016 [paper] [bibtex]
  • Yue Cao, Mingsheng Long, Jianmin Wang, Han Zhu.  Correlation Autoencoder Hashing for Supervised Cross-Modal Search.  International Conference on Multimedia Retrieval, 2016 [paper] [bibtex]
  • Guosheng Lin, Chunhua Shen, Anton van den Hengel.  Supervised Hashing Using Graph Cuts and Boosted Decision Trees.  IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015 [paper] [code] [bibtex]
  • F Shen, C Shen, W Liu, HT Shen.  Supervised Discrete Hashing.  IEEE Conf. Computer Vision and Pattern Recognition, 2015 [paper] [code] [bibtex]
  • Jingkuan Song, Lianli Gao, Yan Yan, Dongxiang Zhang, Nicu Sebe.  Supervised Hashing with Pseudo Labels for Scalable Multimedia Retrieval.  ACM Multimedia Conference, 2015 [paper] [bibtex]
  • Wu-Jun Li, Sheng Wang, Wang-Cheng Kang.  Feature learning based deep supervised hashing with pairwise labels.  arXiv, 2015 [paper] [bibtex]
  • Jile Zhou, Guiguang Ding, Yuchen Guo, Qiang Liu, XinPeng Dong.  Kernel-based supervised hashing for cross-view similarity search.  IEEE International Conference on Multimedia and Expo, 2014 [paper] [bibtex]
  • Jingkuan Song, Yi Yang, Xuelong Li, Zi Huang.  Robust Hashing With Local Models for Approximate Similarity Search.  TOC(Transactions on Cybernetics), 2014 [paper] [bibtex]
  • Guosheng Lin, Chunhua Shen, Qinfeng Shi, Anton van den Hengel, David Suter.  Fast Supervised Hashing with Decision Trees for High-Dimensional Data.  IEEE Conf. Computer Vision and Pattern Recognition, 2014 [paper] [code][bibtex]
  • Dongqing Zhang, Wu-Jun Li.  Large-Scale Supervised Multimodal Hashing with Semantic Correlation Maximization.  AAAI Conference on Artificial Intelligence, 2014 [paper] [bibtex]
  • Viet Anh Nguyen, Jiwen Lu, Minh N Do.  Supervised discriminative hashing for compact binary codes.  ACM Conference on Multimedia, 2014 [paper] [bibtex]
  • Cong Leng, Jian Cheng, Jiaxiang Wu, Xi Zhang, Hanqing Lu.  Supervised hashing with soft constraints.  ACM International Conference on Information and Knowledge Management, 2014 [paper] [bibtex]
  • Tiezheng Ge, Kaiming He, Jian Sun.  Graph Cuts for Supervised Binary Coding.  European Conference on Computer Vision, 2014 [paper] [bibtex]
  • Jian Cheng, Cong Leng, Peng Li, Meng Wang, Hanqing Lu.  Semi-supervised multi-graph hashing for scalable similarity search.  Computer Vision and Image Understanding, 2014 [paper] [bibtex]

Quantization
  • Chao Ma, Ivor W Tsang, Fumin Shen, Chuancai Liu.  Error Correcting Input and Output Hashing.  TOC(Transactions on Cybernetics), 2018 [paper] [bibtex]
  • Yuchen Guo, Guiguang Ding, Jungong Han.  Robust quantization for general similarity search.  IEEE Transactions on Image Processing, 2018 [paper] [bibtex]
  • Jingkuan Song, Lianli Gao, Li Liu, Xiaofeng Zhu, Nicu Sebe.  Quantization-based hashing: a general framework for scalable image and video retrieval.  Pattern Recognition, 2018 [paper] [bibtex]
  • Xiang Wu, Ruiqi Guo, Ananda Theertha Suresh, Daniel N Holtmann-Rice, David Simcha, Felix Yu, Sanjiv Kumar.  Multiscale Quantization for Fast Similarity Search.  Neural Information Processing Systems, 2017 [paper] [bibtex]
  • Litao Yu, Zi Huang, Fumin Shen, Jingkuan Song, Heng Tao Shen, Xiaofang Zhou.  Bilinear optimized product quantization for scalable visual content analysis.  IEEE Transactions on Image Processing, 2017 [paper] [bibtex]
  • Xianglong Liu, Zhujin Li, Cheng Deng, Dacheng Tao.  Distributed adaptive binary quantization for fast nearest neighbor search.  IEEE Transactions on Image Processing, 2017 [paper] [bibtex]
  • Jingjing Liu Liu, Shaoting Zhang, Wei Liu, Cheng Deng, Yuanjie Zheng, Dimitris N. Metaxas.  Scalable Mammogram Retrieval Using Composite Anchor Graph Hashing With Iterative Quantization.  IEEE Transactions on Circuits and Systems for Video Technology, 2017 [paper] [bibtex]
  • Haomiao Liu, Ruiping Wang, Shiguang Shan, Xilin Chen.  Learning Multifunctional Binary Codes for Both Category and Attribute Oriented Retrieval Tasks.  IEEE Conference on Computer Vision and Pattern Recognition, 2017 [paper] [bibtex]
  • Yueqi Duan, Jiwen Lu, Ziwei Wang, Jianjiang Feng, Jie Zhou.  Learning deep binary descriptor with multi-quantization.  IEEE Conference on Computer Vision and Pattern Recognition, 2017 [paper] [bibtex]
  • Zhujin Li, Xianglong Liu, Junjie Wu, Hao Su.  Adaptive Binary Quantization for Fast Nearest Neighbor Search.  The biennial European Conference on Artificial Intelligence, 2016 [paper] [bibtex]
  • Xianglong Liu, Bowen Du, Cheng Deng, Ming Liu, Bo Lang.  Structure sensitive hashing with adaptive product quantization.  TOC(IEEE transactions on cybernetics), 2016 [paper] [bibtex]
  • Qun Chen, Bo Lang, Xianglong Liu, Zepeng Gu.  DisITQ: A Distributed Iterative Quantization Hashing Learning Algorithm.  ISCID(Computational Intelligence and Design), 2016 [paper] [bibtex]
  • Yuchen Guo, Guiguang Ding, Jungong Han, Xiaoming Jin.  Robust iterative quantization for efficient lp-norm similarity search.  International Joint Conferences on Artificial Intelligence, 2016 [paper] [bibtex]
  • Cheng Deng, Huiru Deng, Xianglong Liu, Yuan Yuan.  Adaptive multi-bit quantization for hashing.  Neurocomputing, 2015 [paper] [code][bibtex]
  • Cong Leng, Jian Cheng, Ting Yuan, Xiao Bai, Hanqing Lu.  Learning Binary Codes with Bagging PCA.  Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2014 [paper] [bibtex]
  • Xianglong Liu, Junfeng He, Bo Lang, Shih-Fu Chang.  Hash bit selection: a unified solution for selection problems in hashing.  IEEE Conference on Computer Vision and Pattern Recognition, 2013 [paper] [bibtex]
  • Yunchao Gong, Svetlana Lazebnik.  Iterative quantization: A procrustean approach to learning binary codes.  IEEE Conference on Computer Vision and Pattern Recognition, 2011 [paper] [bibtex]
  • Xianglong Liu, Junfeng He, Bo Lang, Shih-Fu Chang.  Hash bit selection: A unified solution for selection problems in hashing.  IEEE Conference on Computer Vision and Pattern Recognition, 2013 [paper] [code][bibtex]
  • Yunchao Gong, Svetlana Lazebnik, Albert Gordo, Florent Perronnin.  Iterative Quantization: A Procrustean Approach to Learning Binary Codes for Large-scale Image Retrieval.  IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012 [paper] [bibtex]
  • Junfeng He, Sanjiv Kumar, Shih-Fu Chang.  On the difficulty of nearest neighbor search.  ARXIV, 2012 [paper] [bibtex]
  • Yunchao Gong, Sanjiv Kumar, Vishal Verma, Svetlana Lazebnik.  Angular quantization-based binary codes for fast similarity search.  Neural Information Processing Systems, 2012 [paper] [code] [bibtex]
  • Mohammad Norouzi, David J Fleet.  Minimal Loss Hashing for Compact Binary Codes.  International Conference on Machine Learning, 2011 [paper] [bibtex]

Indexing
  • Xianglong Liu, Cheng Deng, Yadong Mu, Zhujin Li.  Boosting Complementary Hash Tables for Fast Nearest Neighbor Search.  AAAI Conference on Artificial Intelligence, 2017 [paper] [bibtex]
  • Xianglong Liu, Cheng Deng, Bo Lang, Dacheng Tao, Xuelong Li.  Query-adaptive reciprocal hash tables for nearest neighbor search.  IEEE Transactions on Image Processing, 2016 [paper] [bibtex]
  • Xianglong Liu, Lei Huang, Cheng Deng, Jiwen Lu, Bo Lang.  Multi-View Complementary Hash Tables for Nearest Neighbor Search.  IEEE International Conference on Computer Vision, 2015 [paper] [bibtex]
  • Xianglong Liu, Junfeng He, Cheng Deng, Bo Lang.  Collaborative hashing.  IEEE Conference on Computer Vision and Pattern Recognition, 2014 [paper][code] [bibtex]
  • Mohammad Norouzi, Ali Punjani, David J. Fleet.  Fast Exact Search in Hamming Space with Multi-Index Hashing.  IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014 [paper] [bibtex]
  • Peng Li, Meng Wang, Jian Cheng, Changsheng Xu, H Lu.  Spectral Hashing with Semantically Consistent Graph for Image Indexing.  ACM Conference on Multimedia, 2013 [paper] [bibtex]
  • Xianglong Liu, Junfeng He, Bo Lang.  Reciprocal Hash Tables for Nearest Neighbor Search.  AAAI Conference on Artificial Intelligence, 2013 [paper] [bibtex]
  • Mohammad Norouzi, Ali Punjani, David J Fleet.  Fast search in hamming space with multi-index hashing.  IEEE Conference on Computer Vision and Pattern Recognition, 2012 [paper] [bibtex]