On a Conjecture Regarding the Adam Optimizer
Not on the map. Why?
Abstract (arXiv)
Why does the Adam optimizer work so well in deep-learning applications? Adam's originators, Kingma and Ba, presented a mathematical argument that was meant to help explain its success, but Bock and colleagues have since reported that a key piece is missing from that argument - an unproven lemma which we will call Bock's conjecture. Here we show that this conjecture is false, but we prove a modified version of it - a generalization of a result of Reddi and colleagues - which can take its place in analyses of Adam.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 7 references that are in the map. First posted on arXiv 16 Nov 2021.
Builds on
4 of 7 references.
References · 4
- 2014Adam: A Method for Stochastic Optimizationcited by 37,240
- 2019On the Convergence of Adam and Beyondcited by 841
- 2018An improvement of the convergence proof of the ADAM-Optimizercited by 19
- 2021Local Convergence of Adaptive Gradient Descent Optimizerscited by 5
Built on by
Not cited yet.