arXiv · 2308.03754
High-Dimensional Non-Convex Landscapes and Gradient Descent Dynamics
Abstract
In these lecture notes we present different methods and concepts developed in statistical physics to analyze gradient descent dynamics in high-dimensional non-convex landscapes. Our aim is to show how approaches developed in physics, mainly statistical physics of disordered systems, can be used to tackle open questions on high-dimensional dynamics in Machine Learning.
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Tony Bonnaire, Davide Ghio, Kamesh Krishnamurthy, Francesca Mignacco, Atsushi Yamamura, Giulio Biroli. 2023-08-07. High-Dimensional Non-Convex Landscapes and Gradient Descent Dynamics. https://arxiv.org/abs/2308.03754
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