January 7, 2010 POSITIVE POLYNOMIALS IN SCALAR AND MATRIX VARIABLES, THE SPECTRAL THEOREM AND OPTIMIZATION

نویسندگان

  • J. WILLIAM HELTON
  • MIHAI PUTINAR
چکیده

This is expanded from the original on behalf of Bill’s classes. We follow a stream of the history of positive matrices and positive functionals, as applied to algebraic sums of squares decompositions, with emphasis on the interaction between classical moment problems, function theory of one or several complex variables and modern operator theory. The second part of the survey focuses on recently discovered connections between real algebraic geometry and optimization as well as polynomials in matrix variables and some control theory problems. These new applications have prompted a series of recent studies devoted to the structure of positivity and convexity in a free ∗-algebra, the appropriate setting for analyzing inequalities on polynomials having matrix variables. We sketch some of these developments, add to them and comment on the rapidly growing literature.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Positive Polynomials in Scalar and Matrix Variables, the Spectral Theorem and Optimization

We follow a stream of the history of positive matrices and positive functionals, as applied to algebraic sums of squares decompositions, with emphasis on the interaction between classical moment problems, function theory of one or several complex variables and modern operator theory. The second part of the survey focuses on recently discovered connections between real algebraic geometry and opt...

متن کامل

Real Algebra, Geometry and Convexity

Gennadiy Averkov (Magdeburg): Lattice-free sets: finiteness and classification results Lattice-free sets are the ‘building blocks’ for cutting-plane type methods in the mixed integer optimization. Recent results in the cutting-plane theory indicate that a complete classification of maximal lattice-free sets is desirable. The talk is mainly devoted to the inclusion-maximal lattice-free sets sati...

متن کامل

Precise Error Analysis of Regularized M-estimators in High-dimensions

A popular approach for estimating an unknown signal x0 ∈ R from noisy, linear measurements y = Ax0 +z ∈ R is via solving a so called regularized M-estimator: x̂ := arg minx L(y−Ax)+λf(x). Here, L is a convex loss function, f is a convex (typically, non-smooth) regularizer, and, λ > 0 is a regularizer parameter. We analyze the squared error performance ‖x̂ − x0‖2 of such estimators in the high-dim...

متن کامل

Competitive Online Algorithms for Resource Allocation over the Positive Semidefinite Cone

We consider a new and general online resource allocation problem, where the goal is to maximize a function of a positive semidefinite (PSD) matrix with a scalar budget constraint. The problem data arrives online, and the algorithm needs to make an irrevocable decision at each step. Of particular interest are classic experiment design problems in the online setting, with the algorithm deciding w...

متن کامل

Nonlinear Knowledge in Spline Models

Support vector machines (SVMs) are a useful tool for learning classifiers or function approximations from data [8, 15, 16, 2, 17, 3, 9]. One important interpretation of SVMs is as an optimization problem in a reproducing-kernel Hilbert space (RKHS) [20, 21]. Recently, prior knowledge in the form of inequalities which must be satisfied over sets of the input space have been added to SVMs for bot...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2010