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
Author(s)
Editors
Chaudhuri, Kamalika
•
Sugiyama, Masashi
Date Issued
2019-04-18
Publisher
Published in
Proceedings of Machine Learning Research
Volume
89
Start page
3225
End page
3233
URL
proceedings
Editorial or Peer reviewed
REVIEWED
Written at
OTHER
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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