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conference paper
Database Alignment with Gaussian Features
Chaudhuri, Kamalika
•
Sugiyama, Masashi
April 18, 2019
Proceedings of Machine Learning Research
We consider the problem of aligning a pair of databases with jointly Gaussian features. We consider two algorithms, complete database alignment via MAP estimation among all possible database alignments, and partial alignment via a thresholding approach of log likelihood ratios. We derive conditions on mutual information between feature pairs, identifying the regimes where the algorithms are guaranteed to perform reliably and those where they cannot be expected to succeed.
Type
conference paper
Authors
Editors
Chaudhuri, Kamalika
•
Sugiyama, Masashi
Publication date
2019-04-18
Publisher
Published in
Proceedings of Machine Learning Research
Volume
89
Start page
3225
End page
3233
URL
proceedings
Peer reviewed
REVIEWED
EPFL units
Event name | Event place | Event date |
Naha, Okinawa, Japan | April 16-18, 2019 | |
Available on Infoscience
March 31, 2020
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