[HN Gopher] Encyclopedia of Optimization
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       Encyclopedia of Optimization
        
       Author : egorpv
       Score  : 50 points
       Date   : 2024-08-13 18:34 UTC (4 days ago)
        
 (HTM) web link (link.springer.com)
 (TXT) w3m dump (link.springer.com)
        
       | fnord123 wrote:
       | > ebook: 1817.93 eur
       | 
       | Wtaf.
        
         | kardos wrote:
         | > Number of Pages
         | 
         | > CCXXXI, 4622
         | 
         | Taf.
        
           | hyperpape wrote:
           | That doesn't really explain an 1800EUR price tag. I've bought
           | 500-100 page encyclopedias of academic subjects for $40 or
           | $50.
           | 
           | Projects like this are built on the work of academics, the
           | majority of whom are publicly funded. By and large they
           | resent the for-profit publishers who benefit from their work
           | and sometimes reduce them to needing to pirate their own
           | work.
        
             | StefanBatory wrote:
             | May I ask you what these encyclopedias were? Purely out of
             | curiosity.
        
             | wakawaka28 wrote:
             | This book is like 7 volumes and 4600 pages on very niche
             | subject matter. It's high but if you need it, you need it.
             | I'm guessing most academics can look up individual papers
             | as needed and don't need a comprehensive summary like this,
             | as nice as that may be.
        
         | mrdude42 wrote:
         | free.99 if you know where to look
        
         | mightysashiman wrote:
         | Lucky you. About 2500CHF in Switzerland. Cute.
        
         | JohnKemeny wrote:
         | It's not meant to be sold as a book, it's available thru your
         | institute's library. The universities pay for them.
        
         | smokel wrote:
         | The hardcover version comes in 7 volumes! [1]
         | 
         | Unfortunately the thing is from 2008 and I suppose this kind of
         | book doesn't age well.
         | 
         | [1]
         | http://titan.princeton.edu/2010-10-11/EoO2/Encyclopedia_Opti...
        
           | wakawaka28 wrote:
           | That's not such a long time for math. There have not been so
           | many innovations in the field since then IMO. Mainly the
           | benchmarks might not be as meaningful, and GPU techniques
           | won't be a big part of that book due to its age.
        
             | mattalex wrote:
             | 2008 is ancient for optimization!
             | 
             | People have tested old year 2000 lp and milp solvers
             | against recent ones while correcting for hardware. Hardware
             | improvements made up ~20x improvement, while lp solvers in
             | general sped up 180x. MILP solvers speed up a full 1000x
             | (Progress in mathematical programming solvers from 2001 to
             | 2020).
             | 
             | Solvers from 2008 are entirely different levels of
             | performance: there are many problems that are unsolvable by
             | those that are solved to zero duality gap in less than a
             | second by more modern solvers.
             | 
             | In MINLPs the difference is even more standing. This
             | doesn't mean that those books are useless (they are quite
             | good), but do not expect a solver based on those techniques
             | to even play in the same league as modern solvers.
        
       | wenc wrote:
       | This is a book about mathematical optimization, not code
       | optimization. It has its place in the world (kinda like an
       | engineering handbook), but the field is constantly evolving and
       | actively researched (especially in frontiers like global
       | optimization and nonlinear nonconvex optimization; linear
       | problems are more mature but still moving at a clip, as witnessed
       | by the vast improvement in solvers over the years).
       | 
       | The danger of indexing too much on a canon of knowledge in a fast
       | evolving field is that you're narrowing your view to a set of
       | techniques that don't work so well on modern problems.
       | 
       | Deep learning for instance is a nonconvex optimization problem
       | where we have a lot of practical knowledge on how to make it work
       | well, but the theoretical knowledge of why it works so well is
       | still being developed. This is a case where practice precedes
       | theory.
       | 
       | Instead of an encyclopedia, I recommend subscribing to a (free)
       | mailing list of pre-prints, Optimization Online.
       | 
       | https://optimization-online.org/
        
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       (page generated 2024-08-17 23:01 UTC)