The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Fast Similarity Search for Learned Metrics
Abstract
We introduce a method that enables scalable similarity search for learned metrics. Given pairwise similarity and dissimilarity constraints between some examples, we learn a Mahalanobis distance function that captures the examples' underlying relationships well. To allow sublinear time similarity search under the learned metric, we show how to encode the learned metric parameterization into randomized locality-sensitive hash functions. We further formulate an indirect solution that enables metric learning and hashing for vector spaces whose high dimensionality makes it infeasible to learn an explicit transformation over the feature dimensions. We demonstrate the approach applied to a variety of image data sets, as well as a systems data set. The learned metrics improve accuracy relative to commonly used metric baselines, while our hashing construction enables efficient indexing with learned distances and very large databases.
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Cites
Distinctive Image Features from Scale-Invariant Keypoints
Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589
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Advances in Neural Information Processing Systems 19
(2007) · The MIT Press eBooks · doi:10.52202/085713 · Cited by 15,539
Nonlinear Dimensionality Reduction by Locally Linear Embedding
Roweis, S. T., & Saul, L. K. (2000) · Science · doi:10.1126/science.290.5500.2323 · Cited by 14,965
A Global Geometric Framework for Nonlinear Dimensionality Reduction
Tenenbaum, J. B., Silva, V. D., & Langford, J. C. (2000) · Science · doi:10.1126/science.290.5500.2319 · Cited by 13,585
Advances in Neural Information Processing Systems 14: Proceedings of the 2001 Conference
(2002) · The MIT Press eBooks · doi:10.7551/mitpress/1120.001.0001 · Cited by 8,890
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
Lazebnik, S., Schmid, C., & Ponce, J. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) · doi:10.1109/cvpr.2006.68 · Cited by 7,916
Dimensionality Reduction by Learning an Invariant Mapping
Hadsell, R., Chopra, S., & LeCun, Y. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) · doi:10.1109/cvpr.2006.100 · Cited by 5,336
Approximate nearest neighbors: towards removing the curse of dimensionality
Indyk, P., & Motwani, R. (1998) · Proceedings of the thirtieth annual ACM symposium on Theory of computing - STOC '98 · doi:10.1145/276698.276876 · Cited by 4,188
Distance Metric Learning for Large Margin Nearest Neighbor Classification
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Cited by
Adapting visual category models to new domains
Saenko, K., Kulis, B., Fritz, M., & Darrell, T. (2010) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-15561-1_16 · Cited by 2,847
Self-citationVisual simultaneous localization and mapping: a survey
Fuentes-Pacheco, J., Ruiz-Ascencio, J., & Rendón-Mancha, J. M. (2015) · Artificial Intelligence Review · doi:10.1007/s10462-012-9365-8 · Cited by 883
What you saw is not what you get: Domain adaptation using asymmetric kernel transforms
Kulis, B., Saenko, K., & Darrell, T. (2011) · CVPR 2011 · doi:10.1109/cvpr.2011.5995702 · Cited by 688
Self-citationA Survey on Metric Learning for Feature Vectors and Structured Data
Bellet, A., Habrard, A., & Sebban, M. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1306.6709 · Cited by 494
Supervised hashing with latent factor models
Zhang, P., Zhang, W., Li, W.-J., & Guo, M. (2014) · Proceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval · doi:10.1145/2600428.2609600 · Cited by 271
Metadata
- Authors
- Kulis, B., Jain, P., & Grauman, K.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2009-12
- Volume
- 31
- Issue
- 12
- Pages
- 2143-2157
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2144892774
- Cited by
- 256
- References
- 61
- FWCI
- 15.39
- Type
- journal article
- Language
- en
- Open access
- closed
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