skip to main content
10.1145/3188745.3188770acmconferencesArticle/Chapter ViewAbstractPublication PagesstocConference Proceedingsconference-collections
research-article
Public Access

Near-optimal linear decision trees for k-SUM and related problems

Published:20 June 2018Publication History

ABSTRACT

We construct near optimal linear decision trees for a variety of decision problems in combinatorics and discrete geometry. For example, for any constant k, we construct linear decision trees that solve the k-SUM problem on n elements using O(n log2 n) linear queries. Moreover, the queries we use are comparison queries, which compare the sums of two k-subsets; when viewed as linear queries, comparison queries are 2k-sparse and have only {−1,0,1} coefficients. We give similar constructions for sorting sumsets A+B and for solving the SUBSET-SUM problem, both with optimal number of queries, up to poly-logarithmic terms.

Our constructions are based on the notion of “inference dimension”, recently introduced by the authors in the context of active classification with comparison queries. This can be viewed as another contribution to the fruitful link between machine learning and discrete geometry, which goes back to the discovery of the VC dimension.

Skip Supplemental Material Section

Supplemental Material

4c-2.mp4

mp4

28.5 MB

References

  1. {AC05} Nir Ailon and Bernard Chazelle. Lower bounds for linear degeneracy testing. Journal of the ACM (JACM), 52(2):157–171, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. {CGI + 16} Marco L Carmosino, Jiawei Gao, Russell Impagliazzo, Ivan Mihajlin, Ramamohan Paturi, and Stefan Schneider. Nondeterministic extensions of the strong exponential time hypothesis and consequences for non-reducibility. In Proceedings of the 2016 ACM Conference on Innovations in Theoretical Computer Science, pages 261–270. ACM, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. {CIO16} Jean Cardinal, John Iacono, and Aurélien Ooms. Solving k-SUM using few linear queries. In 24th Annual European Symposium on Algorithms, ESA 2016, pages 25:1–25:17, 2016.Google ScholarGoogle Scholar
  4. {CL15} Timothy M Chan and Moshe Lewenstein. Clustered integer 3SUM via additive combinatorics. In Proceedings of the Forty-Seventh Annual ACM on Symposium on Theory of Computing, pages 31–40. ACM, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. {DL74} David Dobkin and Richard J Lipton. On some generalizations of binary search. In Proceedings of the sixth annual ACM symposium on Theory of computing, pages 310–316. ACM, 1974. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. {Eri99} Jeff Erickson. Bounds for linear satisfiability problems. Chicago Journal of Theoretical Computer Science, page 8, 1999.Google ScholarGoogle Scholar
  7. {ES17} Esther Ezra and Micha Sharir. A nearly quadratic bound for the decision tree complexity of k-SUM. In 33rd International Symposium on Computational Geometry, SoCG 2017, pages 41:1–41:15, 2017.Google ScholarGoogle Scholar
  8. {Fre76a} Michael L Fredman. How good is the information theory bound in sorting? Theoretical Computer Science, 1(4):355–361, 1976.Google ScholarGoogle ScholarCross RefCross Ref
  9. {Fre76b} Michael L Fredman. New bounds on the complexity of the shortest path problem. SIAM Journal on Computing, 5(1):83–89, 1976.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. {GO95} Anka Gajentaan and Mark H Overmars. On a class of o(n 2 ) problems in computational geometry. Computational geometry, 5(3):165–185, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. {GP14} Allan Grønlund and Seth Pettie. Threesomes, degenerates, and love triangles. In Foundations of Computer Science (FOCS), 2014 IEEE 55th Annual Symposium on, pages 621–630. IEEE, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. {GS17} Omer Gold and Micha Sharir. Improved bounds for 3sum, k-sum, and linear degeneracy. In 25th Annual European Symposium on Algorithms, ESA 2017, pages 42:1–42:13, 2017.Google ScholarGoogle Scholar
  13. {GT62} Eiichi Goto and Hidetosi Takahasi. Some theorems useful in threshold logic for enumerating boolean functions. In IFIP Congress, pages 747–752, 1962.Google ScholarGoogle Scholar
  14. {KLMZ17} Daniel M Kane, Shachar Lovett, Shay Moran, and Jiapeng Zhang. Active classification with comparison queries. arXiv preprint arXiv:1704.03564, 2017.Google ScholarGoogle Scholar
  15. {MadH84} Friedhelm Meyer auf der Heide. A polynomial linear search algorithm for the n-dimensional knapsack problem. Journal of the ACM (JACM), 31(3):668–676, 1984. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. STOC’18, June 25–29, 2018, Los Angeles, CA, USA Daniel M. Kane, Shachar Lovett, and Shay Moran {Mei93} Stefan Meiser. Point location in arrangements of hyperplanes. Information and Computation, 106(2):286–303, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. {Pet02} Seth Pettie. On the comparison-addition complexity of all-pairs shortest paths. In Algorithms and Computation, 13th International Symposium, ISAAC 2002 Vancouver, BC, Canada, November 21-23, 2002, Proceedings, pages 32–43, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. {VC71} VN Vapnik and A Ya Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probability & Its Applications, 16(2):264–280, 1971.Google ScholarGoogle Scholar
  19. {VC15} Vladimir N Vapnik and A Ya Chervonenkis. On the uniform convergence of relative frequencies of events to their probabilities. In Measures of Complexity, pages 11–30. Springer, 2015.Google ScholarGoogle Scholar
  20. {VW15} Virginia Vassilevska Williams. Hardness of easy problems: Basing hardness on popular conjectures such as the strong exponential time hypothesis (invited talk). In LIPIcs-Leibniz International Proceedings in Informatics, volume 43. Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2015.Google ScholarGoogle Scholar
  21. {Wil14} Ryan Williams. Faster all-pairs shortest paths via circuit complexity. In Proceedings of the forty-sixth annual ACM symposium on Theory of computing, pages 664–673. ACM, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. {Yao81} Andrew Chi-Chih Yao. On the parallel computation for the knapsack problem. In Proceedings of the thirteenth annual ACM symposium on Theory of computing, pages 123–127. ACM, 1981. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Near-optimal linear decision trees for k-SUM and related problems

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      STOC 2018: Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing
      June 2018
      1332 pages
      ISBN:9781450355599
      DOI:10.1145/3188745

      Copyright © 2018 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 20 June 2018

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

      Acceptance Rates

      Overall Acceptance Rate1,469of4,586submissions,32%

      Upcoming Conference

      STOC '24
      56th Annual ACM Symposium on Theory of Computing (STOC 2024)
      June 24 - 28, 2024
      Vancouver , BC , Canada

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader