764 research outputs found
Accurate and Efficient Expression Evaluation and Linear Algebra
We survey and unify recent results on the existence of accurate algorithms
for evaluating multivariate polynomials, and more generally for accurate
numerical linear algebra with structured matrices. By "accurate" we mean that
the computed answer has relative error less than 1, i.e., has some correct
leading digits. We also address efficiency, by which we mean algorithms that
run in polynomial time in the size of the input. Our results will depend
strongly on the model of arithmetic: Most of our results will use the so-called
Traditional Model (TM). We give a set of necessary and sufficient conditions to
decide whether a high accuracy algorithm exists in the TM, and describe
progress toward a decision procedure that will take any problem and provide
either a high accuracy algorithm or a proof that none exists. When no accurate
algorithm exists in the TM, it is natural to extend the set of available
accurate operations by a library of additional operations, such as , dot
products, or indeed any enumerable set which could then be used to build
further accurate algorithms. We show how our accurate algorithms and decision
procedure for finding them extend to this case. Finally, we address other
models of arithmetic, and the relationship between (im)possibility in the TM
and (in)efficient algorithms operating on numbers represented as bit strings.Comment: 49 pages, 6 figures, 1 tabl
Estimating the inverse trace using random forests on graphs
Some data analysis problems require the computation of (regularised) inverse
traces, i.e. quantities of the form \Tr (q \bI + \bL)^{-1}. For large
matrices, direct methods are unfeasible and one must resort to approximations,
for example using a conjugate gradient solver combined with Girard's trace
estimator (also known as Hutchinson's trace estimator). Here we describe an
unbiased estimator of the regularized inverse trace, based on Wilson's
algorithm, an algorithm that was initially designed to draw uniform spanning
trees in graphs. Our method is fast, easy to implement, and scales to very
large matrices. Its main drawback is that it is limited to diagonally dominant
matrices \bL.Comment: Submitted to GRETSI conferenc
Toward accurate polynomial evaluation in rounded arithmetic
Given a multivariate real (or complex) polynomial and a domain ,
we would like to decide whether an algorithm exists to evaluate
accurately for all using rounded real (or complex) arithmetic.
Here ``accurately'' means with relative error less than 1, i.e., with some
correct leading digits. The answer depends on the model of rounded arithmetic:
We assume that for any arithmetic operator , for example or , its computed value is , where is bounded by some constant where , but
is otherwise arbitrary. This model is the traditional one used to
analyze the accuracy of floating point algorithms.Our ultimate goal is to
establish a decision procedure that, for any and , either exhibits
an accurate algorithm or proves that none exists. In contrast to the case where
numbers are stored and manipulated as finite bit strings (e.g., as floating
point numbers or rational numbers) we show that some polynomials are
impossible to evaluate accurately. The existence of an accurate algorithm will
depend not just on and , but on which arithmetic operators and
which constants are are available and whether branching is permitted. Toward
this goal, we present necessary conditions on for it to be accurately
evaluable on open real or complex domains . We also give sufficient
conditions, and describe progress toward a complete decision procedure. We do
present a complete decision procedure for homogeneous polynomials with
integer coefficients, {\cal D} = \C^n, and using only the arithmetic
operations , and .Comment: 54 pages, 6 figures; refereed version; to appear in Foundations of
Computational Mathematics: Santander 2005, Cambridge University Press, March
200
Estimating the inverse trace using random forests on graphs
International audienc
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