Database alignment with Gaussian features

Osman Emre Dai, Daniel Cullina, Negar Kiyavash

Research output: Contribution to conferencePaper

Abstract

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.

Original languageEnglish (US)
StatePublished - 2020
Event22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019 - Naha, Japan
Duration: Apr 16 2019Apr 18 2019

Conference

Conference22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019
CountryJapan
CityNaha
Period4/16/194/18/19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Statistics and Probability

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  • Cite this

    Dai, O. E., Cullina, D., & Kiyavash, N. (2020). Database alignment with Gaussian features. Paper presented at 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, Naha, Japan.