Someone wrote “You should look into the behavior of the adaptation signal. I think some guys call it the steering vector. Basically how does the a-priori parts of RLS behave and what can be known before hand with respect to adaptation versus known signals.”
Isn’t the point of the paper to perform a division of labour on the algorithm so that you make a prediction based on reasonable expectations, just like how we drive cars on roads we have never been on at fast speeds with the trust that no one has put a switchback ahead without a sign. Whereas if we are on the backroads we don’t know, we use way more of our attentive energy to focus on curve changes?
In this scenario there would be a detection of road grade change that would alert us to attend to unmarked changes when we encountered grated, and then ungrated terrain.
So the idea here is not to achieve fine precision, but to optimize the appropriate level of calculation in terms of elegance, by detectecting when and when not to apply fine grain monitoring.
If this claim were true, wouldn’t it falsify the paper?