15 citations · 55 across the 17 of their papers we have counts for
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math.OC2016
Local Convergence of the Heavy-ball Method and iPiano for Non-convex Optimization
Peter Ochs
A local convergence result for abstract descent methods is proved. The sequence of iterates is attracted by a local (or global) minimum, stays in its neighborhood and converges wit…
math.OC2016★ 3 cited
Unifying abstract inexact convergence theorems and block coordinate variable metric iPiano
Peter Ochs
An abstract convergence theorem for a class of generalized descent methods that explicitly models relative errors is proved. The convergence theorem generalizes and unifies several…
math.OC2016
Techniques for Gradient Based Bilevel Optimization with Nonsmooth Lower Level Problems
Peter Ochs, René Ranftl, Thomas Brox +1
We propose techniques for approximating bilevel optimization problems with non-smooth lower level problems that can have a non-unique solution. To this end, we substitute the expre…