Landscape and training regimes in deep learning

Event

Weekly DL Theory & Stat Phy Seminar

Short summary

In this seminar, I will talk about a line of works that tries to explain the phase transition behavior of the loss landscape (and the training dynamics as well) as the number of datas and parameters vary from a statistical physics point of view, namely, the jamming transition.

Papers

Paper discussed in the seminar:

  • Mario Geiger, Leonardo Petrini, and Matthieu Wyart. Landscape and training regimes in deep learning. In Physics Report 924:1-18, 2021.
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