Deterministic approximation algorithms for sphere constrained homogeneous polynomial optimization problems

Due to their fundamental nature and numerous applications, sphere constrained polynomial optimization problems have received a lot of attention lately. In this paper, we consider three such problems: (i) maximizing a homogeneous polynomial over the sphere; (ii) maximizing a multilinear form over a Cartesian product of spheres; and (iii) maximizing a multiquadratic form over a Cartesian product of spheres. Since these problems are generally intractable, our focus is on designing polynomial-time approximation algorithms for them. By reducing the above problems to that of determining the L2-diameters of certain convex bodies, we show that they can all be approximated to within a factor of Ω((log n/n)d/2–1) deterministically, where n is the number of variables and d is the degree of the polynomial. This improves upon the currently best known approximation bound of Ω((1/n)d/2–1) in the literature. We believe that our approach will find further applications in the design of approximation algorithms for polynomial optimization problems with provable guarantees.

[1]  S. Sullivant,et al.  Emerging applications of algebraic geometry , 2009 .

[2]  Olga Taussky-Todd SOME CONCRETE ASPECTS OF HILBERT'S 17TH PROBLEM , 1996 .

[3]  Christopher J. Hillar,et al.  Most Tensor Problems Are NP-Hard , 2009, JACM.

[4]  Ravi Kannan,et al.  Spectral methods for matrices and tensors , 2010, STOC '10.

[5]  Stanisław Kwapień,et al.  Decoupling Inequalities for Polynomial Chaos , 1987 .

[6]  Liqun Qi,et al.  Eigenvalues of a real supersymmetric tensor , 2005, J. Symb. Comput..

[7]  Pablo A. Parrilo,et al.  A PTAS for the minimization of polynomials of fixed degree over the simplex , 2006, Theor. Comput. Sci..

[8]  Jiawang Nie An Approximation Bound Analysis for Lasserre’s Relaxation in Multivariate Polynomial Optimization , 2013 .

[9]  Shuzhong Zhang,et al.  Approximation algorithms for homogeneous polynomial optimization with quadratic constraints , 2010, Math. Program..

[10]  Gene H. Golub,et al.  Matrix computations , 1983 .

[11]  Miklós Simonovits,et al.  Deterministic and randomized polynomial-time approximation of radii , 2001 .

[12]  J. G. Pierce,et al.  Geometric Algorithms and Combinatorial Optimization , 2016 .

[13]  Gene H. Golub,et al.  Matrix computations (3rd ed.) , 1996 .

[14]  HE Simai,et al.  General Constrained Polynomial Optimization : an Approximation Approach , 2009 .

[15]  Siep Weiland,et al.  Singular Value Decompositions and Low Rank Approximations of Tensors , 2010, IEEE Transactions on Signal Processing.

[16]  Tamara G. Kolda,et al.  Tensor Decompositions and Applications , 2009, SIAM Rev..

[17]  N. Biggs GEOMETRIC ALGORITHMS AND COMBINATORIAL OPTIMIZATION: (Algorithms and Combinatorics 2) , 1990 .

[18]  Willard Miller,et al.  The IMA volumes in mathematics and its applications , 1986 .

[19]  Peter Gritzmann,et al.  Inner and outerj-radii of convex bodies in finite-dimensional normed spaces , 1992, Discret. Comput. Geom..

[20]  L. Qi,et al.  Conditions for strong ellipticity and M-eigenvalues , 2009 .

[21]  Y. Nesterov Random walk in a simplex and quadratic optimization over convex polytopes , 2003 .

[22]  Wim Michiels,et al.  Recent Advances in Optimization and its Applications in Engineering , 2010 .

[23]  Subhash Khot,et al.  Linear Equations Modulo 2 and the L1 Diameter of Convex Bodies , 2008, 48th Annual IEEE Symposium on Foundations of Computer Science (FOCS'07).

[24]  L. Lathauwer,et al.  On the best low multilinear rank approximation of higher-order tensors , 2010 .

[25]  Chen Ling,et al.  Biquadratic Optimization Over Unit Spheres and Semidefinite Programming Relaxations , 2009, SIAM J. Optim..

[26]  Pierre Comon,et al.  Multiarray Signal Processing: Tensor decomposition meets compressed sensing , 2010, ArXiv.

[27]  P. Parrilo Structured semidefinite programs and semialgebraic geometry methods in robustness and optimization , 2000 .

[28]  Anthony Man-Cho So,et al.  A Unified Theorem on Sdp Rank Reduction , 2008, Math. Oper. Res..

[29]  P. Regalia,et al.  Tensor Approximation and Signal Processing Applications , 2005 .

[30]  Fei Wang,et al.  Z-eigenvalue methods for a global polynomial optimization problem , 2009, Math. Program..

[31]  L. Qi,et al.  Conditions for Strong Ellipticity of Anisotropic Elastic Materials , 2009 .

[32]  Etienne de Klerk,et al.  The complexity of optimizing over a simplex, hypercube or sphere: a short survey , 2008, Central Eur. J. Oper. Res..

[33]  Jean B. Lasserre,et al.  Global Optimization with Polynomials and the Problem of Moments , 2000, SIAM J. Optim..

[34]  Zhi-Quan Luo,et al.  A Semidefinite Relaxation Scheme for Multivariate Quartic Polynomial Optimization with Quadratic Constraints , 2010, SIAM J. Optim..

[35]  Alexander I. Barvinok Integration and Optimization of Multivariate Polynomials by Restriction onto a Random Subspace , 2007, Found. Comput. Math..

[36]  M. Laurent Sums of Squares, Moment Matrices and Optimization Over Polynomials , 2009 .