othercriteria

Karma: 420

othercriteria 28 Oct 2015 22:39 UTC
2 points
in reply to: PhilGoetz’s comment on: The mystery of Brahms
Seconding all of gjm’s criticisms, and adding another point.

The sostenuto (middle) pedal was invented in 1844. The sustain (right) pedal has been around roughly as long as the piano itself, since piano technique is pretty much unthinkable without it.

othercriteria 15 May 2015 17:23 UTC
0 points
in reply to: gwern’s comment on: LW survey: Effective Altruists and donations
The explanation by owencb is what I was trying to address. To be explicit about when the offset is being added, I’m suggesting replacing your log1p(x) ≣ log(1 + x) transformation with log(c + x) for c=10 or c=100.

If the choice of log-dollars is just for presentation, it doesn’t matter too much. But in a lesswrong-ish context, log-dollars also have connotations of things like the Kelly criterion, where it is taken completely seriously that there’s more of a difference between $0 and $1 than between $1 and $3^^^3.

othercriteria 14 May 2015 4:38 UTC
5 points
on: LW survey: Effective Altruists and donations
Given that at least 25% of respondents listed $0 in charity, the offset you add to the charity ($1 if I understand log1p correctly) seems like it could have a large effect on your conclusions. You may want to do some sensitivity checks by raising the offset to, say, $10 or $100 or something else where a respondent might round their giving down to $0 and see if anything changes.

othercriteria 6 May 2015 16:33 UTC
1 point
in reply to: CellBioGuy’s comment on: May 2015 Media Thread
Curtis Yarvin, who looked to Mars for tips and tricks on writing a “tiny, diamond-perfect kernel” for a programming environment.

othercriteria 10 Apr 2015 13:42 UTC
2 points
in reply to: IlyaShpitser’s comment on: How urgent is it to intuitively understand Bayesianism?
The Rasch model does not hate truth, nor does it love truth, but the truth if made out of items which it can use for something else.

othercriteria 11 Mar 2015 0:06 UTC
2 points
in reply to: garabik’s comment on: Harry Potter and the Methods of Rationality discussion thread, March 2015, chapter 119
Not, it’s much more akin to Dennett’s “Where Am I?” or to becoming meguca.

othercriteria 24 Feb 2015 20:46 UTC
2 points
in reply to: palladias’s comment on: Harry Potter and the Methods of Rationality discussion thread, February 2015, chapter 108
This seems like a good occasion to quote the twist reveal in Orson Scott Card’s Dogwalker:

We stood there in his empty place, his shabby empty hovel that was ten times better than anywhere we ever lived, and Doggy says to me, real quiet, he says, “What was it? What did I do wrong? I thought I was like Hunt, I thought I never made a single mistake in this job. in this one job.”

And that was it, right then I knew. Not a week before, not when it would do any good. Right then I finally knew it all, knew what Hunt had done. Jesse Hunt never made mistakes. But he was also so paranoid that he haired his bureau to see if the babysitter stole from him. So even though he would never accidentally enter the wrong P-word, he was just the kind who would do it on purpose. “He doublefingered every time,” I says to Dog. “He’s so damn careful he does his password wrong the first time every time, and then comes in on his second finger.”

“So one time he comes in on the first try, so what?” He says this because he doesn’t know computers like I do, being half-glass myself.

“The system knew the pattern, that’s what. Jesse H. is so precise he never changed a bit, so when we came in on the first try, that set off alarms. It’s my fault, Dog. I knew how crazy paranoidical he is, I knew that something was wrong, but not till this minute I didn’t know what it was. I should have known it when I got his password, I should have known. I’m sorry, you never should have gotten me into this, I’m sorry, you should have listened to me when I told you something was wrong. I should have known, I’m sorry.”

othercriteria 14 Jan 2015 23:42 UTC
1 point
on: Bayesian Utility: Representing Preference by Probability Measures
This seems cool but I have a nagging suspicion that this reduces to greater generality and a handful of sentences if you use conditional expectation of the utility function and the Radon-Nikodym theorem?

othercriteria 4 Dec 2014 15:47 UTC
1 point
in reply to: jamesf’s comment on: December 2014 Media Thread
Noun phrases that are insufficiently abstract.

othercriteria 19 Nov 2014 4:13 UTC
9 points
in reply to: bogus’s comment on: Neo-reactionaries, why are you neo-reactionary?

echo chambers [...] where meaningless duckspeak is endlessly repeated

Imagine how intolerable NRx would be if it were to acquire one of these. Fortunately, their ideas are too extreme for 4chan, even, so I have no idea where such a forum would be hosted.

othercriteria 18 Nov 2014 14:31 UTC
11 points
in reply to: XiXiDu’s comment on: Open thread, Nov. 17 - Nov. 23, 2014
How meaningful is the “independent” criterion given the heavy overlaps in works cited and what I imagine must be a fairly recent academic MRCA among all the researchers involved?

othercriteria 17 Nov 2014 18:56 UTC
16 points
in reply to: Dahlen’s comment on: Open thread, Nov. 17 - Nov. 23, 2014

stupid problem

embarrassingly simple math since forever

I should have been years ahead of my peers

momentary lack of algebraic insight (“I could solve this in an instant if only I could get rid of that radical”)

for which I’ve had the intuitions since before 11th grade when they began teaching it to us

Sorry to jump from object-level to meta-level here but it seems pretty clear that the problem here is not just about math. Your subjective assessments of how difficult these topics are is inconsistent with how well you report you are doing at them. And you’re attaching emotions of shame and panic (“problem has snowballed”) to observations that should just be objective descriptions of where you are now. Get these issues figured out first (unless you’re in some educational setting with its own deadlines). Math isn’t going anywhere; it will still be there when you’re in a place where doing it won’t cause you distress.

othercriteria 14 Nov 2014 17:21 UTC
2 points
in reply to: Capla’s comment on: The “best” mathematically-informed topics?
It’s been a while since I’ve thought about how to learn ecology, but maybe check out Ben Bolker’s Ecological Models and Data in R? It would also be a decent way to start to learn how to do statistics with R.

othercriteria 14 Nov 2014 17:04 UTC
2 points
in reply to: Capla’s comment on: The “best” mathematically-informed topics?
That is important destination but maybe too subtle a starting point.

Start with ecological models for inter-species interactions (predation, competition, mutualism, etc.) where there are more examples and the patterns are simpler, starker, and more intuitive. Roughly, death processes may depend on all involved populations but birth processes depend on each species separately. Then move to natural selection and evolution, intra-species interactions, where the birth processes for each genotype may depend on populations of all the different genotypes, and death processes depend on the phenotypes of all the different populations.

othercriteria 14 Nov 2014 15:05 UTC
0 points
in reply to: Prismattic’s comment on: 2014 Less Wrong Census/Survey
The conscientiousness/akrasia interactions are also fascinating, but even harder to measure. There’s a serious missing-not-at-random censoring effect going on for people too conscientious to leave off digit ratio but too akrasic to do the measurement. I nearly fell into this bucket.

othercriteria 14 Nov 2014 14:44 UTC
5 points
in reply to: IlyaShpitser’s comment on: The “best” mathematically-informed topics?
do what gwern does

Or do the complete opposite.

The impression I get of gwern is that he reads widely, thinks creatively, and experiments frequently, so he is constantly confronted with hypotheses that he has encountered or has generated. His use of statistics is generally confirmatory, in that he’s using data to filter out unjustified hypotheses so he can further research or explore or theorize about the remaining ones.

Another thing you can do with data is exploratory data analysis, using statistics to pull out interesting patterns for further consideration. The workflow for this might look more like:
- Acquire (often multivariate) data from another researcher, source, or experiment.
- Look at its marginal distributions to check your understanding of the system and catch really obvious outliers.
- Maybe use tools like mixture modeling or Box-Cox transformation to clarify marginal distributions.
- Use statistical tools like (linear, logistic, support vector, etc.) regression, PCA, etc., to find patterns in the data.
- Do stuff with the resulting patterns: think up mechanisms, do confirmatory analysis, check literature, show them to other people, etc.
A lot of what you get out of this process will be spurious, but seeing hypotheses that the data seemed to support go down in flames is a good way to convince yourself of the value of confirmatory analysis, and of tools for dealing with this multiple testing problem.

I remember Gelman saying useful stuff like this, but it’s been a while since I read that post so I might be mischaracterizing it.

(Ilya, you know all of this, surely at a deeper level than I do. I’m just rhetorically talking to you as a means to dialogue at Capla. Gwern, hopefully my model of you is not too terrible.)

othercriteria 3 Nov 2014 17:57 UTC
2 points
in reply to: sixes_and_sevens’s comment on: Open thread, Nov. 3 - Nov. 9, 2014
No idea. Factor analysis is the standard tool to see that some instrument (fancy work for ability) is not unitary. It’s worth learning about anyways, if it’s not in your toolbox.

othercriteria 3 Nov 2014 17:53 UTC
8 points
in reply to: Metus’s comment on: Open thread, Nov. 3 - Nov. 9, 2014

Some people like to layer trousers

A simple way to do this is flannel-lined jeans. The version of these made by L.L. Bean have worked well for me. They trade off a bit of extra bulkiness for substantially greater warmth and mildly improved wind protection. Random forum searches suggest that the fleece-lined ones are even warmer, but you lose the cool plaid patterning on the rolled up cuffs.

othercriteria 3 Nov 2014 15:31 UTC
3 points
in reply to: sixes_and_sevens’s comment on: Open thread, Nov. 3 - Nov. 9, 2014
A not quite nit-picking critique of this phenomenon is that it’s treating a complex cluster of abilities as a unitary one.

In some of the (non-Olympic!) distance races I’ve run, it’s seemed to me that I just couldn’t move my legs any faster than they were going. In others, I’ve felt great except for a side stitch that made me feel like I’d vomit if I pushed myself harder. And in still others, I couldn’t pull in enough air to make my muscles do what I wanted. In the latter case, I’d definitely notice the lower oxygen levels but in the former cases, maybe I wouldn’t.

So dial down my oxygen and ask to do a road race? Maybe I’ll notice, maybe I won’t. But ask me to do a decathlon, and some medley swimming, and a biathlon? I bet I’ll notice the low oxygen on at least some of those subtasks, whichever of them that require just the wrong mix of athletic abilities.

For the reading one, I can believe this if I’m doing some light pleasure reading and just trying to push plot into my brain as fast as possible. But if I’m reading math research papers, getting the words and symbols into my head is not the rate-limiting step. If there are some typos in the prose, or even in the results or proofs, it doesn’t make much of a difference. There might be some second-order effects—when I try to fill in details and an equation doesn’t balance, I can be less certain that the error is mine—but these are minor.

So maybe sharpen your claim down to unitary(-ish) abilities?

othercriteria 24 Oct 2014 0:36 UTC
7 points
on: Is this paper formally modeling human (ir)rational decision making worth understanding?
Seconding a lot of calef’s observations.

If the new topic you want to learn is “extended behavior networks”, then maybe this is your best bet. But if you really want to learn about something like AI or ML or the design of agents that behave reasonably by the standards of some utility-like theory, then this is probably a bad choice. A quick search in Google Scholar (if you’re not using this, or some equivalent, making this a step before going to the hivemind is a good idea) suggests that extended behavior networks are backwater-y. If the idea of a network of things interacting to make a decision appeals to you, maybe look into Petri nets or POMDPs. Or better yet, start with something like Russel and Norvig’s AIMA to get a better view of the landscape. If the irrationality part is interesting, start with Kahneman, Slovic, and Tversky’s Judgment under uncertainty: Heuristics and biases, which gives you a curated collection of jargoney papers.