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I really like the sneers about some terrible naming, e.g. in the slide on "The self-attention operation": > “keys”, “queries”, “values”, in one of the least-me
by smokel 3y ago
I really like the sneers about some terrible naming, e.g. in the slide on "The self-attention operation":
> “keys”, “queries”, “values”, in one of the
least-meaningful semantic designations we have in deep learning
And in the context of LSTMs:
> throwing in some other names, like “forget gate”, “input gate”, “output gate” for
good measure
This makes me feel more confident about actually understanding these topics. Before, I was totally misled by the awkward terminology.
- sva_ 3y agoIt gets even worse when you see how the ML community likes to bastardize terms from neuroscience. But I think it is good to have memorable names that one can use to talk about the concepts verbally.
- jeron 3y agosimply operator overloading
- p1esk 3y agoThe names make sense to me once I understood what they represent. How else would you like to call them?
- smokel 3y agoI understand the terminology in the context of the original papers, but to me the metaphors don't seem to generalize well, or at least not in the suggested direction. This is probably just an unfortunate situation, due to progressive understanding. Pointing this out in the slides gave me a sense of relief. Personally, I wouldn't put names to every minor part of an algorithm or formula that was discovered to work empirically. But then again, I haven't discovered anything, and the authors of the respective papers certainly deserve some credit for their inventions!
- visarga 3y ago> “forget gate”, “input gate”, “output gate” These are legit: cell_h = cell_(h-1) * forget_gate + tanh(linear(input_h)) * input_gate out_h = cell_h * output_gate see? forget_gate masks input by multiplying with numbers in [0, 1], input_gate controls the external input, output_gate controls the output of course
- 0cf8612b2e1e 3y agoI also enjoy how ML likes to twist statistical nomenclature enough to be irritating.