I'm surprised to see that our research made it to HN. If you'd like more details, have a look at the derivations [1] and some supplementary case studies [2] that were not published.
Groxx is right: what we're doing is quite simple conceptually, but we did spend a lot of time figuring out what the right system model was (it had to be both widely applicable and tractable). For example, some subtle variations of the current model are very hard to solve.
Awesome, thanks! I'll give them a more thorough read-through some time, it's definitely interesting stuff. I figured my mental model might be over-simplified :) Out of curiosity, are the 'subtle variations' included in the papers, or what might they be? I'm curious where my gaps are.
Exponential (memoryless) propagation delays, for example. In this case, our Gaussian (ie, suboptimal) estimator performs well due to the CLT, but the optimal estimator is hard to compute.
Groxx is right: what we're doing is quite simple conceptually, but we did spend a lot of time figuring out what the right system model was (it had to be both widely applicable and tractable). For example, some subtle variations of the current model are very hard to solve.
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[1]http://www.pedropinto.org.s3.amazonaws.com/publications/loca...
[2]http://www.pedropinto.org.s3.amazonaws.com/publications/loca...