The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Computational Advertising: Techniques for Targeting Relevant Ads
Open accessAbstract
This survey highlights the recent advances in algorithms for numerical linear algebra that have come from the technique of linear sketching, whereby given a matrix, one first compresses it to a much smaller matrix by multiplying it by a (usually) random matrix with certain properties. Much of the expensive computation can then be performed on the smaller matrix, thereby accelerating the solution for the original problem. In this survey we consider least squares as well as robust regression problems, low rank approximation, and graph sparsification. We also discuss a number of variants of these problems. Finally, we discuss the limitations of sketching methods.
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Cites
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ALGORITHMS FOR NON-NEGATIVE MATRIX FACTORIZATION
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ALGORITHMS FOR NON-NEGATIVE MATRIX FACTORIZATION
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Approximate nearest neighbors: towards removing the curse of dimensionality
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Dictionary learning for integrative, multimodal and scalable single-cell analysis
Hao, Y., Stuart, T., Kowalski, M. H., Choudhary, S., Hoffman, P., Hartman, A., Srivastava, A., Molla, G., Madad, S., Fernandez-Granda, C., et al. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-01767-y · Cited by 5,631
Federated Learning: Strategies for Improving Communication Efficiency
Konečný, J., McMahan, H. B., Yu, F. X., Richtárik, P., Suresh, A. T., & Bacon, D. (2016) · arXiv · doi:10.48550/arxiv.1610.05492 · Cited by 3,766
Rodríguez-Barroso, N., Jiménez-López, D., Luzón, M. V., Herrera, F., & Martínez-Cámara, E. (2023) · Information Fusion · doi:10.1016/j.inffus.2022.09.011 · Cited by 296
Tang, E. (2021) · Physical Review Letters · doi:10.1103/physrevlett.127.060503 · Cited by 140
Scalable and Differentially Private Distributed Aggregation in the Shuffled Model
Ghazi, B., Pagh, R., & Velingker, A. (2019) · arXiv · doi:10.48550/arxiv.1906.08320 · Cited by 62
Metadata
- Authors
- Woodruff, D. P.
- Venue
- Foundations and Trends® in Theoretical Computer Science
- Publisher
- Emerald
- Published
- 2014
- Volume
- 10
- Issue
- 1-2
- Pages
- 1-157
- ISSN
- 1551-305X (ISSN-L)
- 1551-3068
- OpenAlex
- W2157988812
- Cited by
- 866
- References
- 61
- FWCI
- 58.61
- Type
- journal article
- Language
- en
- Open access
- green
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