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  4. Database Alignment with Gaussian Features
 
conference paper

Database Alignment with Gaussian Features

Dai, Osman Emre
•
Cullina, Daniel
•
Kiyavash, Negar  
Chaudhuri, Kamalika
•
Sugiyama, Masashi
April 18, 2019
Proceedings of Machine Learning Research
AISTATS

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.

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Type
conference paper
Author(s)
Dai, Osman Emre
Cullina, Daniel
Kiyavash, Negar  
Editors
Chaudhuri, Kamalika
•
Sugiyama, Masashi
Date Issued

2019-04-18

Publisher

MLR Press

Published in
Proceedings of Machine Learning Research
Volume

89

Start page

3225

End page

3233

URL

proceedings

http://proceedings.mlr.press/v89/
Editorial or Peer reviewed

REVIEWED

Written at

OTHER

EPFL units
BAN  
Event nameEvent placeEvent date
AISTATS

Naha, Okinawa, Japan

April 16-18, 2019

Available on Infoscience
March 31, 2020
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/167733
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