Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
184 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

On Symmetric Factorizations of Hankel Matrices (2307.00805v1)

Published 3 Jul 2023 in math.NA, cs.DS, and cs.NA

Abstract: We present two conjectures regarding the running time of computing symmetric factorizations for a Hankel matrix $\mathbf{H}$ and its inverse $\mathbf{H}{-1}$ as $\mathbf{B}\mathbf{B}*$ under fixed-point arithmetic. If solved, these would result in a faster-than-matrix-multiplication algorithm for solving sparse poly-conditioned linear programming problems, a fundamental problem in optimization and theoretical computer science. To justify our proposed conjectures and running times, we show weaker results of computing decompositions of the form $\mathbf{B}\mathbf{B}* - \mathbf{C}\mathbf{C}*$ for Hankel matrices and their inverses with the same running time. In addition, to promote our conjectures further, we discuss the connections of Hankel matrices and their symmetric factorizations to sum-of-squares (SoS) decompositions of single-variable polynomials.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (45)
  1. The generalized Schur algorithm for the superfast solution of Toeplitz systems. In Rational approximation and its applications in mathematics and physics, pages 315–330. Springer, 1987.
  2. Superfast solution of real positive definite Toeplitz systems. SIAM Journal on Matrix Analysis and Applications, 9(1):61–76, 1988.
  3. Iterative refinement for ℓpsubscriptℓ𝑝\ell_{p}roman_ℓ start_POSTSUBSCRIPT italic_p end_POSTSUBSCRIPT-norm regression. In Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 1405–1424. SIAM, 2019.
  4. A refined laser method and faster matrix multiplication. In Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 522–539. SIAM, 2021.
  5. Erwin H Bareiss. Numerical solution of linear equations with Toeplitz and vector Toeplitz matrices. Numerische Mathematik, 13(5):404–424, 1969.
  6. On the stability of the Bareiss and related Toeplitz factorization algorithms. SIAM Journal on Matrix Analysis and Applications, 16(1):40–57, 1995.
  7. An homotopy method for ℓpsubscriptℓ𝑝\ell_{p}roman_ℓ start_POSTSUBSCRIPT italic_p end_POSTSUBSCRIPT regression provably beyond self-concordance and in input-sparsity time. In Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing, pages 1130–1137, 2018.
  8. Pseudospectral shattering, the sign function, and diagonalization in nearly matrix multiplication time. Foundations of Computational Mathematics, pages 1–89, 2022.
  9. Minimum cost flows, MDPs, and ℓ1subscriptℓ1\ell_{1}roman_ℓ start_POSTSUBSCRIPT 1 end_POSTSUBSCRIPT-regression in nearly linear time for dense instances. In Samir Khuller and Virginia Vassilevska Williams, editors, STOC ’21: 53rd Annual ACM SIGACT Symposium on Theory of Computing, Virtual Event, Italy, June 21-25, 2021, pages 859–869. ACM, 2021.
  10. Solving tall dense linear programs in nearly linear time. In Proccedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, STOC 2020, Chicago, IL, USA, June 22-26, 2020, pages 775–788. ACM, 2020.
  11. Jan van den Brand. Complexity term balancer. www.ocf.berkeley.edu/~vdbrand/complexity/. Tool to balance complexity terms depending on fast matrix multiplication.
  12. Jan van den Brand. A deterministic linear program solver in current matrix multiplication time. In Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 259–278. SIAM, 2020.
  13. Joohwan Chun. Fast array algorithms for structured matrices. Stanford University, 1989.
  14. Faster sparse matrix inversion and rank computation in finite fields. In ITCS, 2022.
  15. Electrical flows, laplacian systems, and faster approximation of maximum flow in undirected graphs. In Proceedings of the forty-third annual ACM symposium on Theory of computing, pages 273–282, 2011.
  16. Introduction to algorithms. MIT press, second edition.
  17. Solving linear programs in the current matrix multiplication time. Journal of the ACM (JACM), 68(1):1–39, 2021.
  18. On the asymptotic complexity of matrix multiplication. SIAM Journal on Computing, 11(3):472–492, 1982.
  19. Fast linear algebra is stable. Numerische Mathematik, 108(1):59–91, 2007.
  20. Fast matrix multiplication is stable. Numerische Mathematik, 106(2):199–224, 2007.
  21. Faster approximate lossy generalized flow via interior point algorithms. In Proceedings of the fortieth annual ACM symposium on Theory of computing, pages 451–460, 2008.
  22. Harry Dym. On Hermitian block Hankel matrices, matrix polynomials, the Hamburger moment problem, interpolation and maximum entropy. Integral Equations and Operator Theory, 12(6):757–812, 1989.
  23. Solving sparse rational linear systems. In Proceedings of the 2006 international symposium on Symbolic and algebraic computation, pages 63–70, 2006.
  24. Faster inversion and other black box matrix computations using efficient block projections. In Proceedings of the 2007 international symposium on Symbolic and algebraic computation, pages 143–150, 2007.
  25. Robust and practical solution of laplacian equations by approximate elimination. arXiv preprint arXiv:2303.00709, 2023.
  26. Faster p𝑝pitalic_p-norm regression using sparsity. arXiv preprint arXiv:2109.11537, 2021.
  27. Improved rectangular matrix multiplication using powers of the coppersmith-winograd tensor. In Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 1029–1046. SIAM, 2018.
  28. Mohammad A Hasan. Hankel matrices and their applications to the numerical factorization of polynomials. Journal of Mathematical analysis and applications, 197(2):459–488, 1996.
  29. N. Karmarkar. A new polynomial-time algorithm for linear programming. Combinatorica, 4(4):373–396, 1984.
  30. Displacement ranks of matrices and linear equations. Journal of Mathematical Analysis and Applications, 68(2):395–407, 1979.
  31. Approaching optimality for solving sdd linear systems. SIAM Journal on Computing, 43(1):337–354, 2014.
  32. Displacement structure: theory and applications. SIAM review, 37(3):297–386, 1995.
  33. Inverses of Toeplitz operators, innovations, and orthogonal polynomials. SIAM review, 20(1):106–119, 1978.
  34. Hankel matrices and polynomials. In International Conference on Applied Algebra, Algebraic Algorithms, and Error-Correcting Codes, pages 321–333. Springer, 1987.
  35. Tutorial on the robust interior point method. arXiv preprint arXiv:2108.04734, 2021.
  36. Zipei Nie. Matrix anti-concentration inequalities with applications. In Proceedings of the 54th Annual ACM SIGACT Symposium on Theory of Computing, pages 568–581, 2022.
  37. Victor Pan. Structured matrices and polynomials: unified superfast algorithms. Springer Science & Business Media, 2001.
  38. Solving sparse linear systems faster than matrix multiplication. In Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 504–521. SIAM, 2021.
  39. Volker Strassen et al. Gaussian elimination is not optimal. Numerische mathematik, 13(4):354–356, 1969.
  40. Nearly linear time algorithms for preconditioning and solving symmetric, diagonally dominant linear systems. SIAM Journal on Matrix Analysis and Applications, 35(3):835–885, 2014.
  41. Pravin M. Vaidya. Speeding-up linear programming using fast matrix multiplication (extended abstract). In 30th Annual Symposium on Foundations of Computer Science, Research Triangle Park, North Carolina, USA, 30 October - 1 November 1989, pages 332–337, 1989.
  42. A stabilized superfast solver for indefinite Hankel systems. Linear Algebra and its Applications, 284(1-3):335–355, 1998.
  43. Max A Woodbury. Inverting modified matrices. Statistical Research Group, 1950.
  44. Superfast and stable structured solvers for Toeplitz least squares via randomized sampling. SIAM Journal on Matrix Analysis and Applications, 35(1):44–72, 2014.
  45. A superfast structured solver for Toeplitz linear systems via randomized sampling. SIAM Journal on Matrix Analysis and Applications, 33(3):837–858, 2012.
Citations (2)

Summary

We haven't generated a summary for this paper yet.