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Perturbation confusion in forward automatic differentiation of higher-order functions

Talkat ICFP 2020 · 2020-08-23..08-26· [machine-learning]
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Fielded forward AD systems produce wrong results for derivatives of higher-order functions because tag creation is tied to invoking the derivative operator, not to each actual derivative calculation; the paper shows a simple curried example where a constructed operator D̂ yields a constant zero instead of the true second derivative. The work diagnoses the bug as perturbation confusion in dual-number/tagging machinery and evaluates two fixes: eta expansion to delay fresh tags and a tag-renaming wrapper, both correct but threatening forward-AD complexity guarantees.

AI-written summary · about

  1. 0:00Intro
  2. 1:09Technical Background and Setup
  3. 2:04(1/4) Forward AD-Example
  4. 3:12(2/4) Nesting Derivatives - Perturbation Confusion
  5. 4:24(3/4) Higher-Order AD-What does it mean?
  6. 6:53(4/4) The Amazing Bug - Details Recall
  7. 8:38Solution Idea One: Eta Expansion
  8. 9:09Solution Idea Two: Tag Substitution
  9. 9:34Conclusion
  10. 10:48ACKNOWLEDGEMENTS
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