Marvels and pitfalls of the Langevin algorithm in noisy high-dimensional inference

Gradient-descent-based algorithms and their stochastic versions have widespread applications in machine learning and statistical inference. In this work, we carry out an analytic study of the performance of the algorithm most commonly considered in physics, the Langevin algorithm, in the context of...

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Bibliografski detalji
Glavni autori: Sarao Mannelli, S, Biroli, G, Cammarota, C, Krzakala, F, Urbani, P, Zdeborová, L
Format: Journal article
Jezik:English
Izdano: American Physical Society 2020