If you want to make an analogy to non-convex optimization, what’s the analogue of the thing you’re optimizing for? In the example of medicine, there you don’t seem to be talking about any fixed loss function, you’re just sort of optimizing for expertiness according to other nearby experts. (This may make a big neon sign saying “PageRank” light up in your brain.)
Here, you’re optimizing for quality of expertise that’s expensive to evaluate directly. For example, if you need a particular surgery, you want a good surgeon for that, but can’t try a lot of different ones. Or, if you’re an investor choosing which company/technology/founder to invest a billion dollars into, you can’t just try investing in everyone who applies.
If you want to make an analogy to non-convex optimization, what’s the analogue of the thing you’re optimizing for? In the example of medicine, there you don’t seem to be talking about any fixed loss function, you’re just sort of optimizing for expertiness according to other nearby experts. (This may make a big neon sign saying “PageRank” light up in your brain.)
Here, you’re optimizing for quality of expertise that’s expensive to evaluate directly. For example, if you need a particular surgery, you want a good surgeon for that, but can’t try a lot of different ones. Or, if you’re an investor choosing which company/technology/founder to invest a billion dollars into, you can’t just try investing in everyone who applies.