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> Ω(...) is a standard notation in complexity theory (related to O(...) notation) Yeah that sucks. All of what you're saying is true and sucks. > You don't ha

> Ω(...) is a standard notation in complexity theory (related to O(...) notation) Yeah that sucks. All of what you're saying is true and sucks. > You don't have to spend brain energy finding and remembering what the author said K means. I don't believe this is true, I believe it is the opposite. A small group of people, people who are often not the ones building the libraries from this research, know what these symbols are likely to mean. Adding a simple glossary at the top of what 'Ω' means, etc, would help. > Every letter in Greek and English already have multiple conventional meanings that could appear in the same papers as it is. Yes, that's one of the many reasons why it's a terrible practice. The same symbols can mean different things across papers.

ndriscoll 3y ago
I don't have a CS degree, but I'm pretty sure everyone who does was supposed to have learned what Ω means in this context. My understanding is it's standard within the field, and is a standard part of undergrad CS programs. So I'd expect that someone building libraries for data structures does understand it (or could refresh their memory). And again, with something like Ω, if you don't understand it, a glossary will not help you. It's not going to help to see "f = Ω(g) means `lim inf n->infinity f(n)/g(n) > 0`". Keep in mind this is a paper, not a tutorial on complexity theory. > Yes, that's one of the many reasons why it's a terrible practice. The same symbols can mean different things across papers. They can just like homonyms in other languages, but the meaning is usually clear from context. If you see "probabilitly 1-δ", you can expect that means "close to 100%", and probably "as close as you'd like" by tweaking some parameter that affects δ. Where there is ambiguity, the author typically spells it out. In longer works like books, authors often have an intro chapter/section where they list all of their notation even if it's completely standard with no ambiguity.
- insanitybit 3y ago
  I don't have a CS degree either but I know what Omega means with regards to Big O. I don't think that that should really be required and I don't see why a glossary would be a problem. Omega is used for many things across many maths. > So I'd expect that someone building libraries for data structures does understand it (or could refresh their memory). Why? It's not related to the same skillset. I can and have built data structures from papers and I don't think that memorizing the greek alphabet is a useful prerequisite. > And again, with something like Ω, if you don't understand it, a glossary will not help you. No one is asking for a wikipedia quote. Just "Ω: Referring to the asymptotic complexity bound" or something like that would be fine and provide plenty of context. > If you see "probabilitly 1-δ", you can expect that means "close to 100%" How nice for you but I can not do that.
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kweingar 3y ago
> A small group of people, people who are often not the ones building the libraries from this research, know what these symbols are likely to mean. If you're writing libraries to implement novel data structures fresh from academia, you can read the math. It's just like programming in a sense. I wouldn't say that it's a terrible practice to use symbols like > & | in code because they have different meanings in C and Bourne shell. You just gotta learn the context.
- insanitybit 3y ago
  I've implemented novel data structures from papers before. A glossary would be helpful.

ndriscoll 3y ago

I don't have a CS degree, but I'm pretty sure everyone who does was supposed to have learned what Ω means in this context. My understanding is it's standard within the field, and is a standard part of undergrad CS programs. So I'd expect that someone building libraries for data structures does understand it (or could refresh their memory). And again, with something like Ω, if you don't understand it, a glossary will not help you. It's not going to help to see "f = Ω(g) means `lim inf n->infinity f(n)/g(n) > 0`". Keep in mind this is a paper, not a tutorial on complexity theory. > Yes, that's one of the many reasons why it's a terrible practice. The same symbols can mean different things across papers. They can just like homonyms in other languages, but the meaning is usually clear from context. If you see "probabilitly 1-δ", you can expect that means "close to 100%", and probably "as close as you'd like" by tweaking some parameter that affects δ. Where there is ambiguity, the author typically spells it out. In longer works like books, authors often have an intro chapter/section where they list all of their notation even if it's completely standard with no ambiguity.

insanitybit 3y ago
I don't have a CS degree either but I know what Omega means with regards to Big O. I don't think that that should really be required and I don't see why a glossary would be a problem. Omega is used for many things across many maths. > So I'd expect that someone building libraries for data structures does understand it (or could refresh their memory). Why? It's not related to the same skillset. I can and have built data structures from papers and I don't think that memorizing the greek alphabet is a useful prerequisite. > And again, with something like Ω, if you don't understand it, a glossary will not help you. No one is asking for a wikipedia quote. Just "Ω: Referring to the asymptotic complexity bound" or something like that would be fine and provide plenty of context. > If you see "probabilitly 1-δ", you can expect that means "close to 100%" How nice for you but I can not do that.

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kweingar 3y ago

> A small group of people, people who are often not the ones building the libraries from this research, know what these symbols are likely to mean. If you're writing libraries to implement novel data structures fresh from academia, you can read the math. It's just like programming in a sense. I wouldn't say that it's a terrible practice to use symbols like > & | in code because they have different meanings in C and Bourne shell. You just gotta learn the context.

insanitybit 3y ago
I've implemented novel data structures from papers before. A glossary would be helpful.