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Complexity and Real Computation

TLDR
This chapter discusses decision problems and Complexity over a Ring and the Fundamental Theorem of Algebra: Complexity Aspects.
Abstract
1 Introduction.- 2 Definitions and First Properties of Computation.- 3 Computation over a Ring.- 4 Decision Problems and Complexity over a Ring.- 5 The Class NP and NP-Complete Problems.- 6 Integer Machines.- 7 Algebraic Settings for the Problem "P ? NP?".- 8 Newton's Method.- 9 Fundamental Theorem of Algebra: Complexity Aspects.- 10 Bezout's Theorem.- 11 Condition Numbers and the Loss of Precision of Linear Equations.- 12 The Condition Number for Nonlinear Problems.- 13 The Condition Number in ?(H(d).- 14 Complexity and the Condition Number.- 15 Linear Programming.- 16 Deterministic Lower Bounds.- 17 Probabilistic Machines.- 18 Parallel Computations.- 19 Some Separations of Complexity Classes.- 20 Weak Machines.- 21 Additive Machines.- 22 Nonuniform Complexity Classes.- 23 Descriptive Complexity.- References.

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Extremal Real Algebraic Geometry and A-Discriminants

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Kronecker's and Newton's Approaches to Solving

TL;DR: In this paper, the authors compare the efficiency of symbolic and numerical analysis procedures that solve systems of multivariate polynomial equations, and show upper and lower bounds of the bit length of approximate zeros.

Computational complexity of real valued recursive functions and analog circuits

TL;DR: It is shown that circuits with units that solve differential equations, simple units that add and multiply functions, and units that sense inequalities in a differentiable way, can compute sets of functions that range from the functions computable in linear space to the primitive recursive functions.
Journal ArticleDOI

On the number of minima of a random polynomial

TL;DR: It is shown that most normal random polynomials of fixed degree have only saddle points and the large deviation principle for the spectral value of large random matrices proves this.
Book ChapterDOI

Analytic Root Clustering: A Complete Algorithm Using Soft Zero Tests

TL;DR: This work addresses the basic problem of determining the geometry of the roots of a complex analytic function f, formalized as the root clustering problem, and provides a complete (δ,e)-exact algorithm based on soft zero tests.
References
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Book

Principles of Algebraic Geometry

TL;DR: In this paper, a comprehensive, self-contained treatment of complex manifold theory is presented, focusing on results applicable to projective varieties, and including discussion of the theory of Riemann surfaces and algebraic curves, algebraic surfaces and the quadric line complex.
Book

The algebraic eigenvalue problem

TL;DR: Theoretical background Perturbation theory Error analysis Solution of linear algebraic equations Hermitian matrices Reduction of a general matrix to condensed form Eigenvalues of matrices of condensed forms The LR and QR algorithms Iterative methods Bibliography.
Book

Theory of Linear and Integer Programming

TL;DR: Introduction and Preliminaries.
Proceedings ArticleDOI

The complexity of theorem-proving procedures

TL;DR: It is shown that any recognition problem solved by a polynomial time-bounded nondeterministic Turing machine can be “reduced” to the problem of determining whether a given propositional formula is a tautology.
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