Correlation clustering in data streams
- Submitting institution
-
The University of Warwick
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 5890
- Type
- E - Conference contribution
- DOI
-
-
- Title of conference / published proceedings
- International Conference on Machine Learning
- First page
- 2237
- Volume
- 37
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- -
- Year of publication
- 2015
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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4
- Research group(s)
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D - Data Science, Systems and Security
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work was the first to showing streaming algorithms for the popular problem of correlation clustering. Published in a top machine learning conference, this well cited research has been used as the basis of a new algorithm in "Improved Massively Parallel Computation Algorithms for MIS, Matching, and Vertex Cover" from ETHZ, MIT, EPFL and Bristol in PODC 2018, and has been selected as one of twenty papers presented in the "Recent Trends in Correlation Clustering" survey. An extended version of this paper has recently been accepted for publication in the Algorithmica journal.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -