Questions tagged [na.numerical-analysis]

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What infinite sums cannot be approximated in polynomial time?

The following is from the book Geometric algorithms and combinatorial optimization: It shows an infinite sum that has an FPTAS (= an $\epsilon$-approximation can be computed using poly($1/\epsilon$) ...
• 2,212
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Complexity of, given any elementary function $f$ and a natural $n$, compute $n$ digits of $f(x)$

We define problem $A$ as follows. Each instance of the problem consists of: (a) some succinct codification of an elementary function, that is, a function constructed by composing arithmetic operators, ...
1 vote
36 views

What is the complexity of the "characteristic bisection" method?

The characteristic bisection method is an algorithm for finding approximate zeros of multi-dimensional functions. It is a generalization of the bisection method; it is described briefly here. ...
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Computing an approximate root of a two-dimensional monotone function

Let $f$ be a Lipschitz-continuous function from the square $[-1,1]^2$ to itself, satisfying the following conditions: For all $y\in [-1,1]$: $~~~~f(-1,y)_1\leq 0\leq f(1,y)_1$, and $f(x,y)_1$ is ...
• 2,212
51 views

Error analysis of Estrin's method

Estrin's Method is an alternative to Horner's method for evaluating polynomials. To evaluate a polynomial $P(x)=\sum_{i=0}^7 a_i x^i$ at a point $x\in\mathbb R$, it first computes the powers $x^2$ and ...
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1 vote
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Interval arithmetic adapted to backwards stable problems

In numerical analysis, there are algorithms which are either forwards stable or backwards stable. Forwards stability is strictly stronger, and is more desirable. Unfortunately, it is in many instances ...
• 303
104 views

Can finite difference methods approximate the space/time complexity of given programs?

While benchmarking a language prototype, I realized that I had a superlinear implementation of a test program, but wasn't sure if it was quadratic or cubic. I stayed up too late and wrote half a page ...
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1 vote
70 views

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146 views

Graph sparsification and eigenspaces

I am currently trying to understand whether I can make some claims about the relation between eigenspaces of a sparsifier and the original matrix. In this context, let me first define a couple of ...
• 118
229 views

What is the time complexity of increasing the precision of finding matrix eigenvalues?

There are various algorithms that output the eigenvalues of an $n \times n$ matrix in time $O(n^3)$. However, I can't find anywhere that tells me about the precision of the output of the algorithm. ...
874 views

Is there any algorithm to find just the largest eigenvalue with subquadratic time complexity?

SVD or PCA can be used find the largest eigenvalue, but at a cost of $O(n^3)$ complexity. Lanczos algorithm runs much faster on a sparse matrix with complexity $O(dn^2)$ where $d$ is the average ...
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Density of multiples

I have an infinite collection of positive integers $n_1,n_2,n_3,\ldots$ and I would like to find the density of the numbers divisible by one or more of these.* If the density does not exist, the ...
• 1,735
2k views

129 views

What's the state of the art for matrix nuclear/trace norm optimization

I am interested in simple matrix optimizations with nuclear/trace norm: $\min_X \left(f(X) + \|X\|_*\right)$ where $\|X\|_*$ stands for the trace norm of the matrix $X$, and $f$ is a convex smooth ...
• 71
1 vote
268 views

Most optimal parallel method for calculating the integral of a 2D function

I posted already this question to SO but got no answer so I try it now here: In some crunching number program, I have a function which can be just 1 or 0 in three dimensions. I do not know in advance ...
• 321
1 vote
134 views

Optimal parallel algorithm for finding roots of a function [closed]

In some problem I need to find the zeroes (multiple real solutions) of some functions in 1D and 2D. I wonder which is the best parallel algorithm for this, which can provide the highest accuracy and ...
• 321
1 vote
129 views

High Dimensional Volume (HDV) estimator for Entropy estimation

I am writing a program using high-dimensional volume (HDV) estimator to estimate entropy and mutual information for variable selection. Let $D = (x^i_1, x^i_2, ..., x^i_M)$, N is the number of data ...
• 11
140 views

What's new in sparse eigensystems solution

As a part of other work I need to solve relatively large (~1E5x1E5) and sparse (~100 non-zero elements in each raw in few blocks) hermitian eigensystems. Usually only few eigenvalues+vectors are ...
• 171
432 views

LU factorization of a 0-1 matrix

I have a rather naive question on LU factorization which probably should be easy to answer. Say I have a matrix with entries only from $\{0,1\}$. When can we expect to get an LU factorization of such ...
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561 views

Iterative algorithms in algebraic complexity (Blum-Shub-Smale-Model)

I know the Blum-Shub-Smale model. It is claimed to provide a theoretical framework for algorithms in real and complex algebra and analysis. A very general question: Most algorithms compromise of ...
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1 vote
110 views

Is there a technique where a square grid is used to as a mesh for time dependent partial differential equations (PDEs) but which the points are permuted in such a way as to minimize error? e.g., ...
146 views

Scaling procedures to address false 0's after multiplying probabilities

I need to translate a training algorithm that involves sums and multiplications of probabilities to actual code. For that I need some sort of scaling procedure that allows me to avoid underflows, that ...
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Complexity of Finding the Eigendecomposition of a *Symmetric* Matrix

This is a specialized version of a previous question: Complexity of Finding the Eigendecomposition of a Matrix . For NxN symmetric matrices, it is known that O(N^3) time suffices to compute the ...
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My question is simple: What is the worst-case running time of the best known algorithm for computing an eigendecomposition of an $n \times n$ matrix? Does eigendecomposition reduce to matrix ...