Thresholds of descending algorithms in inference problems
This is an incremental review aimed at physicists, summarizing existing results without new contributions.
The paper reviews recent works that analyze the dynamics of gradient-based algorithms in statistical inference problems, using methods from glassy systems physics to understand their performance quantitatively and qualitatively.
We review recent works on analyzing the dynamics of gradient-based algorithms in a prototypical statistical inference problem. Using methods and insights from the physics of glassy systems, these works showed how to understand quantitatively and qualitatively the performance of gradient-based algorithms. Here we review the key results and their interpretation in non-technical terms accessible to a wide audience of physicists in the context of related works.