Re:Stanford Lecture Notes on Probabilistic Graphical Models
by utkarshsinha on Tuesday April 25, 2017 @12:24AM
(#14190760)
You're wrong. What you're suggesting is there is no merit in going for an O(n^2) sorting algorithm to O(nlogn) and then to an O(n^1.2534) sorting algorithm.
SLAM at a multi-city scale can use mathematical trickery to improve runtime. Sure, a new solver would help - but we don't need it as long as there is another trick up the mathematician's sleeve. Oh, and it's harder to come up with a new solver / technique.
But Dellaert didn't invent Factor Graphs, nor how to map a Factor Graphs to a Least Squares problem. Others did that way before him.
My criticism is directed towards his style of writing about SLAM in terms of probabilities and densities, which, IMO, is moot since at the end of the day he's just using Gaussians as everyone else and hence everything boils down to a Least Squares problem again. His probabilistic viewpoint is just a detour, a distraction at that point.
If he contributed a different kind of solver that could deal with arbitrary distributions then his probabilistic viewpoint would make a whole lot more sense but as long as it's just Gaussians I just don't see the point.