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Notice that this subject has an almost total overlap with what is called "graph signal processing", yet the terminology sounds completely different.
by enriquto 7y ago
Notice that this subject has an almost total overlap with what is called "graph signal processing", yet the terminology sounds completely different.
- mehrdadn 7y agoWow. I just Googled and found a graph Fourier Transform (GFT). Amazing. https://arxiv.org/pdf/1712.00468.pdf https://arxiv.org/pdf/1712.00468.pdf
- adamnemecek 7y agoFourier is gonna be big for representation discovery in reinforcement learning.
- joe_the_user 7y agoYes, This sort of thing intrigues me tremendously and I'm going over the text. At the same time, I always have a certain "what could you really get" feeling about systems that begin with machinery from objects with lots of structure (differentiable manifolds) and generalize and generalize until it is dealing a structure that seems utterly arbitrary. I mean, locally, "almost everywhere" (and similar caveats), the characteristics of a point of a differentiable manifold determine "nearly everything" about the points in its neighborhood. Oppositely, one node of graph no necessary relation to the next node. So what exactly do we get from our complex machinery? Are the theorem ultimately more about "summation processes on graphs" than graphs?
- adamnemecek 7y agoI think it's about operators and adjoints. http://www.reproducibility.org/RSF/book/bei/conj/paper_html/index.html http://www.reproducibility.org/RSF/book/bei/conj/paper_html/...