Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional
Inference

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Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference

21 December 2018

Stefano Sarao Mannelli

Florent Krzakala

Pierfrancesco Urbani

Lenka Zdeborová

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Papers citing "Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference"

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Title
The Role of the Time-Dependent Hessian in High-Dimensional Optimization Tony Bonnaire Giulio Biroli C. Cammarota 162 0 0 04 Mar 2024
Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective Davide Ghio Yatin Dandi Florent Krzakala Lenka Zdeborová DiffM 102 33 0 27 Aug 2023
Learning Single-Index Models with Shallow Neural Networks A. Bietti Joan Bruna Clayton Sanford M. Song 256 74 0 27 Oct 2022
Large-N dynamics of the spiked tensor model with random initial conditions V. Sazonov 55 0 0 26 Aug 2022
Sudakov-Fernique post-AMP, and a new proof of the local convexity of the TAP free energy Michael Celentano 116 22 0 19 Aug 2022
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling Gerard Ben Arous Reza Gheissari Aukosh Jagannath 194 65 0 08 Jun 2022
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks Blake Bordelon Cengiz Pehlevan MLT 126 99 0 19 May 2022
High-dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models Tengyuan Liang Subhabrata Sen Pragya Sur 113 7 0 09 Apr 2022
Origami in N dimensions: How feed-forward networks manufacture linear separability Christian Keup M. Helias 111 9 0 21 Mar 2022
Selective Multiple Power Iteration: from Tensor PCA to gradient-based exploration of landscapes M. Ouerfelli M. Tamaazousti V. Rivasseau 101 7 0 23 Dec 2021
On the Cryptographic Hardness of Learning Single Periodic Neurons M. Song Ilias Zadik Joan Bruna AAML 93 31 0 20 Jun 2021
Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems Stefano Sarao Mannelli Pierfrancesco Urbani 149 10 0 23 Feb 2021
Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification Francesca Mignacco Florent Krzakala Pierfrancesco Urbani Lenka Zdeborová MLT 136 70 0 10 Jun 2020
Information-theoretic limits of a multiview low-rank symmetric spiked matrix model Jean Barbier Galen Reeves 135 15 0 16 May 2020
Thresholds of descending algorithms in inference problems Stefano Sarao Mannelli Lenka Zdeborova AI4CE 125 4 0 02 Jan 2020
Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model Stefano Sarao Mannelli Giulio Biroli C. Cammarota Florent Krzakala Lenka Zdeborová 89 44 0 18 Jul 2019
Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models Stefano Sarao Mannelli Florent Krzakala Pierfrancesco Urbani Lenka Zdeborová 184 51 0 01 Feb 2019