View Single Post
  #2  
Old 04-21-2013, 07:02 AM
Michael Reach Michael Reach is offline
Senior Member
 
Join Date: Apr 2013
Location: Baltimore, Maryland, USA
Posts: 71
Default Re: Why 2^N Makes Learning Unfeasible

I think that's right. You want to be able to make \epsilon small.

Note that this doesn't mean that learning is not feasible, only that this inequality won't help you prove that it is. There might be some other way to bound growth. The professor already hinted that there are sometimes more ways, based on an "average" growth function that works for "most" cases.
Reply With Quote