3 ms·
> the data generating process (us) gave the data those properties People in the space say that all the time, or else don't say it because they're talking with
by uoaei 3y ago
> the data generating process (us) gave the data those properties
People in the space say that all the time, or else don't say it because they're talking with others who they know already understand that fact, rather than posting about it on HN in public.
HN feels like you have access to experts but it's often the case that experts don't have the time nor patience to teach grad-level classes in comment threads to clear up confusion. So the people who do post are either talking about something specific in a way that presumes a certain level of base knowledge or are frankly bullshitting.
There's a certain cultural heritage on HN, maybe across broad swaths of the tech world IRL, of speaking purely speculatively but phrasing it as presumed fact. I call this behavior "high-school debate club" but the more classical name for it is Dunning-Kruger. It seems to have a regrettably outsized effect on the discourse in the more influential (if still naive) echelons of tech, either as an extension of a broad blind optimism or as a way to stave off feelings of loneliness that are pervasive in these industries by appealing to and seeking approval of the prestigious community that HN is purported to be.
- Cupertino95014 3y agoDunning-Kruger is a college professor who pronounces truth to the heathen in a condescending way.
- mjburgess 3y agoYou'd be surprised at the vast array of PhDs who've entered this space through conversion courses from essentially non-technical backgrounds -- that end-up repeating essentially mystical pseudoscience. There's lots of papers, vast numbers, that very clearly miss basic premises about the data generating process; and about what exactly we're modelling and how. Premises drilled into statisticians, and so on -- but omitted from a computer science education; and esp. from much of the route into these fields today. Absent these, the process, i'm sure, appears very mystical. This paper ought ask, "what assumptions about the data generating process ought we make such that these regularisation conditions work" I really do think that the question isnt phrased this way due to "too much kool-aid" --- its a paper which seems, to me, to already buy into a kind of mystification. Though, this may just be a symptom of not thinking about the problem from the pov of formal/traditional stats. The paper seems to be wanting some sort of "cute conceptual answer" that might appear in a hand-wavey ML paper But the answer is to specify families of distributions whose semantic and non-sematic structures are "accessible" by these unsupervised techniques -- find which families do not work, which ones do... and then formulate an essentially psych-social hypothesis as to why the people creating htat data have used those distributions