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Mar 13, 2017 at 16:36 comment added Anton Petrunin @Mehrdad, no, there are no interesting examples; this is easy to check.
Mar 13, 2017 at 5:56 comment added user541686 @AntonPetrunin: If I understand this example correctly, the subgradient (1,0) can be approximated arbitrarily well by a convex combination of gradients in a ball around (0,0)... so we might as well call it a subgradient, right? If so, it seems a bit like telling someone that $\max x : x < 1$ doesn't exist... which is true, but not all that interesting. Are there any interesting counterexamples, or are they all correct if we're willing to take reasonable limits as needed?
Aug 6, 2016 at 23:38 comment added Austin Bren Thanks for the responses. Does this fact go for when we have gradients almost everywhere on the ball (and subgradients on the non-differentiable points)? Also, any citations or literature to go with this?
Aug 6, 2016 at 22:32 comment added Anton Petrunin @TravisHartford, in this case it is true. In fact if the gradient is defined at all points of a small sphere then any subgradient inside is a convex combination of at most $n+1$ of gradients on the sphere.
Aug 6, 2016 at 22:11 comment added Austin Bren I wonder if there is also an example where all $x$ within the unit ball are defined for the function. I feel that this example only works (it is a valid counterexample) because there are undefined points in the ball.
Aug 6, 2016 at 22:09 vote accept Austin Bren
Aug 6, 2016 at 22:05 vote accept Austin Bren
Aug 6, 2016 at 22:09
S Aug 6, 2016 at 20:45 history suggested Fabian Wirth CC BY-SA 3.0
Fixed grammar and took care of a typo.
Aug 6, 2016 at 20:24 review Suggested edits
S Aug 6, 2016 at 20:45
Aug 6, 2016 at 14:34 history answered Anton Petrunin CC BY-SA 3.0