[HN Gopher] A Theory of Universal Learning [pdf] ___________________________________________________________________ A Theory of Universal Learning [pdf] Author : emre Score : 40 points Date : 2020-11-09 19:11 UTC (3 hours ago) (HTM) web link (web.math.princeton.edu) (TXT) w3m dump (web.math.princeton.edu) | bra-ket wrote: | Calling this 'universal learning' is a stretch (and in HN speak | 'click-bait'). The paper only talks about a particular subclass | of learning algorithms in supervised learning domain within PAC | framework. | | Specially they talk about learning algorithms that minimize some | error function from training examples. That's not how learning | happens in living organisms. Therefore calling it 'universal' is | an unwarranted generalization, kind of like 'theory of | everything'. | | A more appropriate name would be 'Distribution-dependent | Supervised PAC Learning' or something along those lines. It's a | solid work which addresses a particular niche of a particular | theory. ___________________________________________________________________ (page generated 2020-11-09 23:02 UTC)