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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Main Authors: Sarao Mannelli, S, Biroli, G, Cammarota, C, Krzakala, F, Urbani, P, Zdeborová, L
格式: Journal article
语言:English
出版: American Physical Society 2020