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Inertial Newton Algorithms Avoiding Strict Saddle Points

Camille Castera 1 
1 IRIT-SC - Signal et Communications
IRIT - Institut de recherche en informatique de Toulouse
Abstract : We study the asymptotic behavior of second-order algorithms mixing Newton's method and inertial gradient descent in non-convex landscapes. We show that, despite the Newtonian behavior of these methods, they almost always escape strict saddle points. We also evidence the role played by the hyper-parameters of these methods in their qualitative behavior near critical points. The theoretical results are supported by numerical illustrations.
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Preprints, Working Papers, ...
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Contributor : Camille Castera Connect in order to contact the contributor
Submitted on : Wednesday, November 17, 2021 - 4:08:08 PM
Last modification on : Monday, July 4, 2022 - 8:43:37 AM


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  • HAL Id : hal-03433202, version 1
  • ARXIV : 2111.04596


Camille Castera. Inertial Newton Algorithms Avoiding Strict Saddle Points. 2021. ⟨hal-03433202⟩



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