So I think I've genuinely finished http://gwern.net/Mail%20delivery now. It should be an interesting read for LWers: it's a fully Bayesian decision-theoretic analysis of when it is optimal to check my mail for deliveries. I learned a tremendous amount working my way through it, from how to much better use JAGS to how to do Bayesian model comparison & averaging to loss functions and EVSI and EVPI for decision theory purposes to even dabbling in reinforcement learning with Thompson sampling/probability-matching.
I thought it was done earlier, but then I realized I had messed up my Thompson sampling implementation and also vectorspace alien pointed out that my algorithm for deciding what datapoint to sample for maximizing information gain was incorrect & how to fix it, and I have made a lot of other small improvements like more images.
Related to this, I am trying to get a subreddit going for statistical decision theory links and papers to discuss: https://www.reddit.com/r/DecisionTheory/
Right now it's just me dumping in decision-theory related material like cost-benefit analyses, textbooks, relevant blog posts, etc, but hopefully other people will join in. We have flair and a sidebar now! If anyone wants to be a mod, just ask. (Workload should be negligibly small, this is more so the subreddit doesn't get locked by absence.)
If it's worth saying, but not worth its own post (even in Discussion), then it goes here.
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