rwilson4

11 ms·

61.
by rwilson4 7y ago
Early on as a manager I made the mistake of assuming I knew what was going on in someone’s head just by working closely with them. I was wrong. You can’t even just directly ask because of the complicated dynamics. The best way I have found
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by rwilson4 7y ago
I treat them as prompts. I’ll give my team as much fore notice as possible what the topic will be and ask them to really think about the question in advance. Otherwise the conversations are often shallow. My team often writes out their thou
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by rwilson4 7y ago
My 1:1s have the following format: - Current tasks - Career development/Goals (we have 6 week and yearly goals that the employees select for themselves with a little guidance from me) - Special topic, different each time and very much
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by rwilson4 7y ago
Skip the first 50 pages or so. The rest is golden.
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by rwilson4 7y ago
Credit where it’s due though. The low barrier to entry and habit-forming nature got me learning Italian. I’m definitely not fluent but I can have conversations with people in cafes and restaurants and it’s pretty fun! Recently I’ve moved on
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by rwilson4 7y ago
It also seems to ignore strike price and the scenario of an acquisition where only the VC and founders get paid.
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by rwilson4 7y ago
Counterpoint: regularization is just a way of specifying a Bayesian prior for maximum a posteriori estimation.
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by rwilson4 7y ago
Anecdotally, SpaceX pays less than other aerospace companies. Source: I used to work at Boeing, I have friends at SpaceX and various other aerospace companies.
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by rwilson4 7y ago
I love how it’s from 2016 and still has NOTESSSS comments.
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by rwilson4 7y ago
Very cool! Any stats you can share about increased performance switching to go?
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by rwilson4 8y ago
I was skeptical about the “applied” part, but glancing through it, the examples are really interesting! Discussing magnetic fields in the same chapter as lambda calculus, very cool! Seems a bit light on details though...
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by rwilson4 8y ago
Using the techniques described on my blog [0], which are ideal for KPIs like conversion rates and small sample sizes (since no Gaussian approximation is made), I get a p-value of 0.177, which is not significant. The observed treatment effec
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by rwilson4 8y ago
Discussion from last time: https://news.ycombinator.com/item?id=19075599
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by rwilson4 8y ago
Lots of practical challenges for sure!
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by rwilson4 8y ago
You're right, and in some instances it is possible to draw causal conclusions from observational data. See [0] and [1] for two pretty different perspectives. But for this to work, you need a lot of data: both lots of units (e.g. people
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by rwilson4 8y ago
Yes absolutely! Random assigment along with statistical power and significance considerations does indeed allow one to draw causal conclusions. It’s the gold standard for causal inference.
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by rwilson4 8y ago
It’s a paradox because many people find it counterintuitive. It’s the mathematical statement of why correlation does not imply causation. The existence of a confounding variable correlated both with the purported cause (eg gender) and the p
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by rwilson4 8y ago
Short, to-the-point, and I wasn't familiar with any of these options! Love it!
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by rwilson4 8y ago
Differences in notation between different fields abound. It used to be (probably still is) the math department didn’t talk to the engineering department, so people would reinvent basically the same solution in different contexts. Now people
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by rwilson4 8y ago
That’s a good point! I’ve typically piggy-backed off these types of systems to do that kind of analysis. But you’re right it is a distinct use case.
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by rwilson4 8y ago
Events are the cornerstone of product analytics. If you want to understand what your users are doing on your platform, and to look for opportunities to improve the user experience, events are a big part of that.
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Rotations, Orientations, and Their Representations(adventuresinwhy.com)
2 points by rwilson4 8y ago|0 comments
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by rwilson4 8y ago
Super cool! Out of curiosity, is this an academic group or a (potentially hiring?) company? Update: After some internet stalking, might be related to JPL? I’d love to hear some meta info about this project: why it was created, what you’re d
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by rwilson4 8y ago
This is all good info; I'll add that a confidence interval on the effect size[0] is more informative than a p-value. (This is subtly different than a confidence interval on the response in each group, which is discussed in the article:
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by rwilson4 8y ago
We definitely do study specific instances. For example, the other day an article was posted here on Support Vector Machines, which are a convex optimization problem having a special structure that is exploitable for fast solutions. For more
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by rwilson4 8y ago
Yes, all constrained optimization problems can be converted to unconstrained problems. For example, consider: minimize f(x) subject to x \in C Let g(x)=f(x) if x \in C and infinity otherwise. Then minimize g(x) has the same solution as the
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by rwilson4 8y ago
SVMs are a convex optimization problem, which means any local optimum is also globally optimal. In practice that leads to fast, provably optimal solutions. With deep learning, the problem is non-convex, so the results are locally optimal bu
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by rwilson4 8y ago
I think people end up reaching for straws because a lot of this stuff works well in practice and they’re trying to make sense of it. 20 years from now we’ll have a much clearer picture of why the techniques work! Until then, a lot of the ex
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by rwilson4 8y ago
Science is a combination of theory and experiment. Sometimes theory advances faster than experiment, sometimes vice versa. Right now in ML, experiment aka practice is advancing faster than theory. Theory will eventually catch up.
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by rwilson4 8y ago
I do donate to homeless shelters and cancer research foundations, and I hope other people are also donating to causes important to them! But I don’t have enough money to make a dent in the problem. Collective action is the only way to make

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