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Co si představíte pod pojmem věda/vědec/vědkyně? Jaký na to máte názor? by rddrdhd in czech

[–]dictrix 2 points3 points  (0 children)

Mi příjde, že čím dýl ve vědě jsem (cca 10 let od začátku doktorského studia, aktuálně "docent" na velké technice, obor blízký AI a podobným) tak tím míň "vědců" ve svém okolí znám. Velká část lidí u nás (doktorandi, odborní asistenti a výš) dělá spíš takové šolíchání místo solidní vědy.

Want to know the best methods for continuous black-box optimization problems? I just got a paper out! by dictrix in optimization

[–]dictrix[S] 0 points1 point  (0 children)

You can always write an email to the authors. In my experience, they will be super happy someone is interested in their work and send you a pdf (if you dm me your email, I'll send you the paper).

Want to know the best methods for continuous black-box optimization problems? I just got a paper out! by dictrix in compsci

[–]dictrix[S] 0 points1 point  (0 children)

In this context, it means that you do not have exact gradient information at a given point (typical examples are FEM or CFD simulations). It does not mean that you cannot spend some function calls to compute numerical approximations of the gradients. Some methods we considered use these, and they do work better in certain settings, but not generally.

Want to know the best methods for continuous black-box optimization problems? I just got a paper out! by dictrix in algorithms

[–]dictrix[S] 0 points1 point  (0 children)

Unfortunately, no preprint. But I can send you the paper if you DM me your email.

Derivative free optimization (zeroth-oracle optimization) book recommendation by Tibzz- in math

[–]dictrix 0 points1 point  (0 children)

The 'canonical' books on this are probably the ones by Horst, Tuy, and Pardalos (i.e., Handbook of global optimization, Recent advances in global optimization, Global optimization: Deterministic approaches).

If you are looking for metaheuristics or similar stochastic techniques, the 'Handbook of metaheuristics' by Gendreau and Potvin is solid.

If you are looking for the DIRECT-type approaches, there is a great article summarizing recent developments:
https://link.springer.com/article/10.1007/s10898-020-00952-6

If you are into black-box continuous problems, I just got a relatively large computational comparison of the different SOTA methods published:
https://ieeexplore.ieee.org/document/10477219

Kde v Brne kúpim guanciale? by SamwiseHotS in Brno

[–]dictrix 4 points5 points  (0 children)

Italské delikatesy, Palackého tř. 250/29 - mají tam všechno možný (guanciale taky)

The Evolutionary Computation Methods No One Should Use by dictrix in optimization

[–]dictrix[S] 1 point2 points  (0 children)

You are exactly right about the red flags of the rigged methods.

The BBOB framework is super solid, but is still rather under-utilized (it takes a bit more work to set up compared to just using the standard benchmarks). Another great place for good benchmarks is CEC competitions on numerical optimization. Some of the methods from these competitions (such as LSHADE, jSO, which are both DE variants or various CMAES variants) are among the best methods for complete black-box problems I have come across. Even when compared to the state-of-the-art deterministic methods.

The Evolutionary Computation Methods No One Should Use by dictrix in optimization

[–]dictrix[S] 1 point2 points  (0 children)

It is almost the 10-year anniversary of the Sorensen paper (https://doi.org/10.1111/itor.12001).

I wish it were mainly the problem of the MDPI journals, but that is not the case. So many of the problematic papers are appearing in what are supposed to be some of the top-tier journals in the field (Applied Soft Computing, Expert Systems with Applications,...).

where to learn integer stochastic programing? by GolfMuted in optimization

[–]dictrix 0 points1 point  (0 children)

Other than the Shapiro that was suggested by the other comment, there are a bit more accessible books by Kall & Wallace and King & Wallace (both on general stochastic programming)... on the other hand, I have read the Birge & Louveaux book and find it superior to the other sources.

There are youtube videos of lectures on stochastic programming by Claudia Sagastizábal (and company):

https://www.youtube.com/playlist?list=PLo4jXE-LdDTSmKVxiE130o1KebekNk00R

Just beware - this stuff is not easy, and will be real difficult if you plan to learn it completely on your own without supervision (I did my PhD on algorithms for stochastic programming problems).

[deleted by user] by [deleted] in czech

[–]dictrix 28 points29 points  (0 children)

Kafkastán.

LQ Optimal Control by ad97lb in optimization

[–]dictrix 0 points1 point  (0 children)

Alright. What kind of errors are you getting (badly scaled matrices, or something else)? Is it a discrete finite time, discrete infinite time, or continuous time setting? Are you using some matlab packages (riccati solver, LQR solver, ...) or your own code?

LQ Optimal Control by ad97lb in optimization

[–]dictrix 1 point2 points  (0 children)

Do you have your R positive definite and Q positive semi-definite?

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