Fast and Exact Outlier Detection in Metric Spaces-Reference-Cited by-同舟云学术

Fast and Exact Outlier Detection in Metric Spaces

Published:2021-06-09 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2021 International Conference on Management of Data
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Author:

Amagata Daichi¹,Onizuka Makoto²,Hara Takahiro²

Affiliation:

1. Osaka University & PRESTO, Suita, Osaka, Japan

2. Osaka University, Suita, Osaka, Japan

Funder

JST CREST

JST PRESTO

JSPS Grant-in-Aid for Scientific Research (A)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3448016.3452782

Reference37 articles.

1. Charu C Aggarwal. 2015. Outlier Analysis. In Data Mining. 237--263. Charu C Aggarwal. 2015. Outlier Analysis. In Data Mining. 237--263.

2. Daichi Amagata and Takahiro Hara. 2021. Fast Density-Peaks Clustering: Multicore-based Parallelization Approach. In SIGMOD . Daichi Amagata and Takahiro Hara. 2021. Fast Density-Peaks Clustering: Multicore-based Parallelization Approach. In SIGMOD .

3. Daichi Amagata Makoto Onizuka and Takahiro Hara. 2021. Fast and Exact Outlier Detection in Metric Spaces: A Proximity Graph-based Approach. https://github.com/amgt-d1/Paper/blob/master/sigmod2021--11-full.pdf . Daichi Amagata Makoto Onizuka and Takahiro Hara. 2021. Fast and Exact Outlier Detection in Metric Spaces: A Proximity Graph-based Approach. https://github.com/amgt-d1/Paper/blob/master/sigmod2021--11-full.pdf .

4. Dolphin: An Efficient Algorithm for Mining Distance-based Outliers in Very Large Datasets;Angiulli Fabrizio;ACM Transactions on Knowledge and Data Discovery,2009

5. Approximate Nearest Neighbor Queries in Fixed Dimensions;Arya Sunil;SODA,1993

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