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From Michael Wechner <michael.wech...@wyona.com>
Subject Re: Rendering Latex Snippets using XSL-FO and FOP
Date Fri, 24 Jan 2014 09:21:44 GMT
Thanks very much for the pointer. Seems to work only with

FOP 0.95beta or 0.95

but I think we are still using 0.93 and I guess we could upgrade ;-)

IIUC probably more effort is to transform Latex to MathML in order to
use this library, but maybe I misunderstand something. Will have a
closer look at it.

Thanks

Michael

Am 24.01.14 10:14, schrieb Luis Bernardo:
> This is not very recent, but take a look at
> http://jeuclid.sourceforge.net/trunk/jeuclid-fop/index.html.
>
>
>
> On Fri, Jan 24, 2014 at 8:54 AM, Michael Wechner
> <michael.wechner@wyona.com>wrote:
>
>> Hi
>>
>>
>> http://www.mathjax.org/
>>
>> which is a great library to render Latex snippets inside HTML. See for
>> example the abstract contained by
>>
>> http://projecteuclid.org/euclid.aos/1388545673
>>
>> I would like to do the "same" thing with PDF, which means I have an XML
>> containing Latex snippets, e.g.
>>
>> <p>
>> We study sparse principal components analysis in high dimensions, where
>> $p$ (the number of variables) can be much larger than $n$ (the number of
>> observations), and analyze the problem of estimating the subspace
>> spanned by the principal eigenvectors of the population covariance
>> matrix. We introduce two complementary notions of $\ell_{q}$ subspace
>> sparsity: row sparsity and column sparsity. We prove nonasymptotic lower
>> and upper bounds on the minimax subspace estimation error for $0\leq >> q\leq1$. The bounds are optimal for row sparse subspaces and nearly
>> optimal for column sparse subspaces, they apply to general classes of
>> covariance matrices, and they show that $\ell_{q}$ constrained estimates
>> can achieve optimal minimax rates without restrictive spiked covariance
>> conditions. Interestingly, the form of the rates matches known results
>> for sparse regression when the effective noise variance is defined
>> appropriately. Our proof employs a novel variational $\sin\Theta$
>> theorem that may be useful in other regularized spectral estimation
>> problems.
>> </p>
>>
>> and then I would like to use XSL-FO and FOP to generate PDF.
>>
>> Is that possible somehow? Or any other ideas how I could generate such a
>> PDF?
>>
>> Thanks
>>
>> Michael
>>
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