Algorithmic and optimization aspects of brascamp-lieb inequalities, via operator scaling

Ankit Garg, Leonid Gurvits, Rafael Oliveira, Avi Wigderson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Scopus citations

Abstract

The celebrated Brascamp-Lieb (BL) inequalities and their reverse form of Barthe are an important mathematical tool, unifying and generalizing numerous inequalities in analysis, convex geometry and information theory, with many used in computer science. While their structural theory is very well understood, far less is known about computing their main parameters (which we later define below). Prior to this work, the best known algorithms for any of these optimization tasks required at least exponential time. In this work, we give polynomial time algorithms to compute: (1) Feasibility of BL-datum, (2) Optimal BL-constant, (3) Weak separation oracle for BL-polytopes. What is particularly exciting about this progress, beyond the better understanding of BL-inequalities, is that the objects above naturally encode rich families of optimization problems which had no prior efficient algorithms. In particular, the BL-constants (which we efficiently compute) are solutions to non-convex optimization problems, and the BL-polytopes (for which we provide efficient membership and separation oracles) are linear programs with exponentially many facets. Thus we hope that new combinatorial optimization problems can be solved via reductions to the ones above, and make modest initial steps in exploring this possibility. Our algorithms are obtained by a simple efficient reduction of a given BL-datum to an instance of the Operator Scaling problem defined by Gurvits. To obtain the results above, we utilize the two (very recent and different) algorithms for the operator scaling problem (by Garg et al. and Ivanyos et al.). Our reduction implies algorithmic versions of many of the known structural results on BL-inequalities, and in some cases provide proofs that are different or simpler than existing ones. Further, the analytic properties of the algorithm by Garg et al. provide new, effective bounds on the magnitude and continuity of BL-constants, with applications to non-linear versions of BL-inequalities; prior work relied on compactness, and thus provided no bounds. On a higher level, our application of operator scaling algorithm to BL-inequalities further connects analysis and optimization with the diverse mathematical areas used so far to motivate and solve the operator scaling problem, which include commutative invariant theory, non-commutative algebra, computational complexity and quantum information theory.

Original languageEnglish
Title of host publicationSTOC 2017 - Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing
EditorsPierre McKenzie, Valerie King, Hamed Hatami
PublisherAssociation for Computing Machinery
Pages397-409
Number of pages13
ISBN (Electronic)9781450345286
DOIs
StatePublished - 19 Jun 2017
Externally publishedYes
Event49th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2017 - Montreal, Canada
Duration: 19 Jun 201723 Jun 2017

Publication series

NameProceedings of the Annual ACM Symposium on Theory of Computing
VolumePart F128415
ISSN (Print)0737-8017

Conference

Conference49th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2017
Country/TerritoryCanada
CityMontreal
Period19/06/1723/06/17

Bibliographical note

Publisher Copyright:
© 2017 Copyright held by the owner/author(s).

Keywords

  • Brascamp-Lieb
  • Inequalities
  • Operator scaling
  • Optimization

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