salaries in Europe are low, even for high-tech jobs, compared to the US. You have to think about the following:
1. Every job has an on-the-job training part. Will you get enough of this kind of training in Europe?
2. The first years of your employment are crucial in determining the growth of your salary in the future, on the average. In Europe, wages are low compared to the US, even in high-tech jobs.
Well, these people should come to Europe, where it's all about fundamental research and no product-oriented research, nice food and cities and people, and no worries for tenure.
Am I the only one who thinks this is kind of a joke? Half of us are confortable in their linux boxes, and the other half in their shiny macs. Who cares what features an already obsolete OS will have in 2016 when it's going to be released?
This is exactly the comment that I was looking for. Bravo, very insightful! Google sits in a browser which in turn sits in an operating system. MS lost the browser battle long time ago, and now plays the card of the operating system. And it is precisely this dependence that will cut the 'air supply'... or maybe not: google adsense is based in context sensitive ads, that are put in websites, especially independent (non-corporate) ones. And it is precisely this dependence that will keep MS in a lower level than google on this matter.
It was also used in the Soviet era for planning manufacturing activities, transportation of goods between the Soviet states, etc.
The 1975 Nobel in Economics went actually to LP and its contribution to the understanding of these activities. Some people expressed their 'outrage' for not including Dantzig in the laureates.
Incidentally, the Simplex method -- unlike differential calculus-based methods for more general problems like the Kuhn-Tucker method -- is quite programmable on a computer, and quite efficient.
In theory, the simplex method is a non-polynomial-time (NP) algorithm, and actually of the worst kind. It is an extremely clever algorithm: it jumps from point to point in order to check whether it is optimal or not, and it can do so exhaustively and in a coherent way. However, it has to check many many points, so many that in theory is the worst thing you can apply to an LP problem.
However, it works quite efficient in practice, and for reasonable problem sizes it spits the solution very fast so that someone can put a simplex solver in a loop and bootstrap it with no remorse.
Of course, nowadays, Interior Point Methods dominate the picture. They are polynomial-time (P) algorithms, they work extremely fast, and they are also very very reliable.
Ok, there is currently a great deal of information over the net for TeX, LaTeX, and derivatives. Knuth is the authoritative guide, useful for the mechanics of typesetting and the internals of the whole system. LaTeX is an augmented set of macros useful in preparing articles, books, reports, even letters.
And since O'Reilly is THE source of educational material in computing, they DO have a book about TeX but it is out of print. It explains how TeX distributions such as TeXLive, the official distribution by TeX User's Group work, and how to put the constituent parts such as BiBTeX (the bibliographic management software).
So much for history. As far as the resources part is concerned, Google is your eternal friend.
No, you can't. You cannot investigate the source, just the script that uses the compiled objects. You cannot see the source of the objects.
Do you know what is meant by ``open source''?
Octave is a nice MATLAB clone, developed from chemical engineers in the beginning, but now used extensively in virtually any area that math is usefull.
Many packages have their open source counterparts: Octave for MATLAB, R-system for SPLUS (statistics algebra system), and so forth. But IMHO you raise another issue:
you can use each of these packages to do whatever calculations you want, since all of them are extended in the C/Fortran end, i.e. they can use programs written in these languages. Custom code is readily integrated. And above all, the GNU Scientific Library. If you don't like or you don't trust the numerical solvers integrated in MATLAB, you can investigate the source in the GSL.
And yes, you can use all of these together. So, what is the question again?
Slashdot Mirror
salaries in Europe are low, even for high-tech jobs, compared to the US. You have to think about the following:
1. Every job has an on-the-job training part. Will you get enough of this kind of training in Europe?
2. The first years of your employment are crucial in determining the growth of your salary in the future, on the average. In Europe, wages are low compared to the US, even in high-tech jobs.
Well, these people should come to Europe, where it's all about fundamental research and no product-oriented research, nice food and cities and people, and no worries for tenure.
Am I the only one who thinks this is kind of a joke? Half of us are confortable in their linux boxes, and the other half in their shiny macs. Who cares what features an already obsolete OS will have in 2016 when it's going to be released?
See Donald Knuth's "Structured Programming with GOTO Statements" (Computing Surveys, Vol 6 Nr. 4 December 1974).
PDF : http://pplab.snu.ac.kr/courses/adv_pl05/papers/p261-knuth.pdf
This is exactly the comment that I was looking for. Bravo, very insightful! Google sits in a browser which in turn sits in an operating system. MS lost the browser battle long time ago, and now plays the card of the operating system. And it is precisely this dependence that will cut the 'air supply' ... or maybe not: google adsense is based in context sensitive ads, that are put in websites, especially independent (non-corporate) ones. And it is precisely this dependence that will keep MS in a lower level than google on this matter.
It was also used in the Soviet era for planning manufacturing activities, transportation of goods between the Soviet states, etc.
The 1975 Nobel in Economics went actually to LP and its contribution to the understanding of these activities. Some people expressed their 'outrage' for not including Dantzig in the laureates.
Quote:
Incidentally, the Simplex method -- unlike differential calculus-based methods for more general problems like the Kuhn-Tucker method -- is quite programmable on a computer, and quite efficient.
In theory, the simplex method is a non-polynomial-time (NP) algorithm, and actually of the worst kind. It is an extremely clever algorithm: it jumps from point to point in order to check whether it is optimal or not, and it can do so exhaustively and in a coherent way. However, it has to check many many points, so many that in theory is the worst thing you can apply to an LP problem.
However, it works quite efficient in practice, and for reasonable problem sizes it spits the solution very fast so that someone can put a simplex solver in a loop and bootstrap it with no remorse.
Of course, nowadays, Interior Point Methods dominate the picture. They are polynomial-time (P) algorithms, they work extremely fast, and they are also very very reliable.
Ok, there is currently a great deal of information over the net for TeX, LaTeX, and derivatives. Knuth is the authoritative guide, useful for the mechanics of typesetting and the internals of the whole system. LaTeX is an augmented set of macros useful in preparing articles, books, reports, even letters.
And since O'Reilly is THE source of educational material in computing, they DO have a book about TeX but it is out of print. It explains how TeX distributions such as TeXLive, the official distribution by TeX User's Group work, and how to put the constituent parts such as BiBTeX (the bibliographic management software).
So much for history. As far as the resources part is concerned, Google is your eternal friend.
No, you can't. You cannot investigate the source, just the script that uses the compiled objects. You cannot see the source of the objects. Do you know what is meant by ``open source''?
Octave is a nice MATLAB clone, developed from chemical engineers in the beginning, but now used extensively in virtually any area that math is usefull.
Many packages have their open source counterparts: Octave for MATLAB, R-system for SPLUS (statistics algebra system), and so forth. But IMHO you raise another issue: you can use each of these packages to do whatever calculations you want, since all of them are extended in the C/Fortran end, i.e. they can use programs written in these languages. Custom code is readily integrated. And above all, the GNU Scientific Library. If you don't like or you don't trust the numerical solvers integrated in MATLAB, you can investigate the source in the GSL.
And yes, you can use all of these together. So, what is the question again?