Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise
Name
farias21a.pdf
Description
Published version
Size
5.55 MB
Format
Adobe PDF
Checksum (MD5)
70a95eaaec28b224d97109f8648cc772
Author(s)
Farias, Vivek F
Li, Andrew A
Peng, Tianyi
Date Issued
2021
Journal
INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139
Citation
Farias, Vivek F, Li, Andrew A and Peng, Tianyi. 2021. "Near-Optimal Entrywise Anomaly Detection for Low-Rank Matrices with Sub-Exponential Noise." INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139, 139.
Version
Final published version
MIT Department
Sloan School of Management
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://proceedings.mlr.press/v139/farias21a.html
