Yes, I should probably clarify and amend my argument. My impression of the article is that it suggests if ergonomic APIs were more available than they already are, then the frequency with which we see bugs in…
Curious why you used Box-Muller for normal PRNGs instead of Ziggurat.
A Uniform(0, 1) PRNG is the right primitive on which to base a PRNG library for arbitrary real-valued random variables because any real-valued random variable can be represented as an inverse quantile transform of a…
I'm not sure I follow why your argument changes the relevance of convexity? If the problems were convex, I don't think we'd be having this discussion -- first-order methods would tend to win.
I'm skeptical as to whether zeroth-order methods really lend themselves to a Bitter Lesson argument. First-order methods don't explore the loss landscape optimally, but the loss function tends to be nonconvex, and…
Even for non-smooth or discontinuous objectives, I'd still reach for methods that use gradient-like information over zeroth-order methods. For non-smooth objectives, Clarke-generalized subdifferentials have been pretty…
Pixi uses uv as a backend, and I've enjoyed the UI because it's easy to add task aliases for things like nicely-formatted lists of outdated packages. (I have no affiliation with the project.) Pixi-diff-to-markdown in…
I don't disagree about the complicity. However, biology and statistics, even at intro level, have had significant updates in material covered over the last 10-20 years. More subtly, terminology changes. My copy of…
My opinion of Gwern's piece is that some of the arguments he makes don't require correlations. For example, A/B tests of differences in means using a zero difference null hypothesis will reject the null, given enough…
Are you referring to the first figure, from Smith, et al, 2007? If so, I couldn't evaluate whether gwern's claim makes sense without reading that paper to get an idea of, e.g., sample size and how they control for false…
As you yourself point out, a consistent estimator of a parameter converges to that parameter's value in the infinite sample limit. That limit is zero or it's not.
A frequentist interpretation of inference assumes parameters have fixed, but unknown values. In this paradigm, it is sensible to speak of the statement "this parameter's value is zero" as either true or false. I do not…
Reporting effect size mitigates this problem. If observed effect size is too small, its statistical significance isn't viewed as meaningful.
I don't disagree with the title, but I'm left wondering what they want us to do about it beyond hinting at causal inference. I'd also be curious what the author thinks of minimum effect sizes (re: Implication 1) and…
Permutation tests don't account for family-wise error rate effects, so I'm curious why you would say that "it doesn't overcorrect like traditional methods". I'm also curious why you say those "cover every case", because…
> Most companies don't cost peoples' lives when you get it wrong. True, but it usually costs money to fix it. I think the themes of "this only matters if lives are on the line" or "it's too rigorous" are straw-men. We…
Yes, I should probably clarify and amend my argument. My impression of the article is that it suggests if ergonomic APIs were more available than they already are, then the frequency with which we see bugs in…
Curious why you used Box-Muller for normal PRNGs instead of Ziggurat.
A Uniform(0, 1) PRNG is the right primitive on which to base a PRNG library for arbitrary real-valued random variables because any real-valued random variable can be represented as an inverse quantile transform of a…
I'm not sure I follow why your argument changes the relevance of convexity? If the problems were convex, I don't think we'd be having this discussion -- first-order methods would tend to win.
I'm skeptical as to whether zeroth-order methods really lend themselves to a Bitter Lesson argument. First-order methods don't explore the loss landscape optimally, but the loss function tends to be nonconvex, and…
Even for non-smooth or discontinuous objectives, I'd still reach for methods that use gradient-like information over zeroth-order methods. For non-smooth objectives, Clarke-generalized subdifferentials have been pretty…
Pixi uses uv as a backend, and I've enjoyed the UI because it's easy to add task aliases for things like nicely-formatted lists of outdated packages. (I have no affiliation with the project.) Pixi-diff-to-markdown in…
I don't disagree about the complicity. However, biology and statistics, even at intro level, have had significant updates in material covered over the last 10-20 years. More subtly, terminology changes. My copy of…
My opinion of Gwern's piece is that some of the arguments he makes don't require correlations. For example, A/B tests of differences in means using a zero difference null hypothesis will reject the null, given enough…
Are you referring to the first figure, from Smith, et al, 2007? If so, I couldn't evaluate whether gwern's claim makes sense without reading that paper to get an idea of, e.g., sample size and how they control for false…
As you yourself point out, a consistent estimator of a parameter converges to that parameter's value in the infinite sample limit. That limit is zero or it's not.
A frequentist interpretation of inference assumes parameters have fixed, but unknown values. In this paradigm, it is sensible to speak of the statement "this parameter's value is zero" as either true or false. I do not…
Reporting effect size mitigates this problem. If observed effect size is too small, its statistical significance isn't viewed as meaningful.
I don't disagree with the title, but I'm left wondering what they want us to do about it beyond hinting at causal inference. I'd also be curious what the author thinks of minimum effect sizes (re: Implication 1) and…
Permutation tests don't account for family-wise error rate effects, so I'm curious why you would say that "it doesn't overcorrect like traditional methods". I'm also curious why you say those "cover every case", because…
> Most companies don't cost peoples' lives when you get it wrong. True, but it usually costs money to fix it. I think the themes of "this only matters if lives are on the line" or "it's too rigorous" are straw-men. We…