Open Peer Review. Open Publishing. Open Access. Open Discussion. Open Directory. Open Recommendations. Open API. Open Source.
Achieving linear or quadratic convergence on piecewise smooth optimization problems
Andreas Griewank, Andrea Walther
Nov 03, 2017 (modified: Nov 03, 2017)NIPS 2017 Workshop Autodiff Submissionreaders: everyone
Abstract:Many problems in machine learning involve objective functions that
are piecewise smooth due to the occurrence of absolute values mins and maxes in
their evaluation procedures. For such function we derived first
order (KKT) and second order (SSC) optimality conditions, which can be checked on
the basis of a local piecewise linearization that can be computed in an AD like
fashion, e.g. using ADOL-C or Tapenade.
Enter your feedback below and we'll get back to you as soon as possible.