Article 71295 of sci.math:
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From: Laura Helen
Newsgroups: sci.math
Subject: Re: Sci.math.grad -- preliminary proposal
Date: Sun, 10 Mar 1996 13:54:36 -0800
Organization: University of California, Los Angeles
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On 10 Mar 1996, Jeff Erickson wrote:
> Laura Helen writes:
> >Subjects like algebraic geometry, group theory
> >at an advanced level, differential geometry, algebraic topology, etc.
> >would be considered "graduate-level".
>
> There's an obvious bias for "pure" "continuous" mathematics here.
> Where would combinatorics fit into this newsgroup? Numerical
> analysis? Statistics? Discrete geometry? Number theory?
The list of graduate-level subjects is not intended to be
exhaustive. Yes, the subjects you mentioned would be acceptable --
any *mathematical* discussion at a graduate level would be
acceptable. I imagine numerical analysis shades into software
engineering, etc. questions -- e.g. "How can I make this algorithm
more efficient" or "Will this random number generator be biased
if I do it single-precision" -- such questions would
have a better place in another newsgroup, but questions of
graduate-level mathematical interest would be welcome.
Article 71305 of sci.math:
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From: jeffleader@aol.com (Jeffleader)
Newsgroups: sci.math
Subject: Num. Analysis is math.! (was Re: Sci.math.grad -- preliminary proposal)
Date: 10 Mar 1996 18:38:37 -0500
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>I imagine numerical analysis shades into software
>engineering, etc. questions -- e.g. "How can I make this algorithm
>more efficient"
Numerical methods shades into software eng., whatever that term
might mean. Numerical analysis has plenty of analysis in it. Making
the DFT more efficient leads to the FFT, a nontrivial bit of math. The
theory of convergence and stability of numerical methods and of error
estimation, for example, involve "hard" math. Finite differences leads
directly to Kreiss matrix theorem, etc. A surprising number of big-name
numerical analysts knew little about programming etc.--they are/were
doing analysis. While an undergraduate level finite differences/elements
for undergraduate engineers (like I must give next quarter) might have a
large programming emphasis as a way of getting two things taught for
the price of one, in all my graduate level num. analysis training we did
no programming--we were doing num. *analysis*. It shouldn't be
confused with a programmer implementing something and trying to eke
out a little more speed or use a little less memory or something. Think
Lax Equivalence Thm., Kreiss Matrix Thm., etc., instead.
Article 71551 of sci.math:
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Newsgroups: sci.math
Subject: Re: Num. Analysis is math.! (was Re: Sci.math.grad -- preliminary proposal)
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From: adler@pulsar.wku.edu (Allen Adler)
Date: 12 Mar 1996 04:11:53 GMT
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In-reply-to: jeffleader@aol.com's message of 10 Mar 1996 18:38:37 -0500
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In his sensible posting on numerical analysis, Jeff Leader writes:
>Think Lax Equivalence Thm., Kreiss Matrix Thm., etc., instead.
Perhaps someone would be kind enough to state these and other
main theorems of numerical analysis.
Allan Adler
adler@pulsar.cs.wku.edu