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Stochastic Gradient Descent outperforms Gradient Descent in recovering a high-dimensional signal in a glassy energy landscape., and . CoRR, (2023)Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem., , and . Mach. Learn. Sci. Technol., 2 (3): 35029 (September 2021)Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification., , , and . NeurIPS, (2020)Approximate Survey Propagation for Statistical Inference., , , and . CoRR, (2018)The effective noise of Stochastic Gradient Descent., and . CoRR, (2021)The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture., , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 6874-6883. PMLR, (2020)Fractal free energy landscapes in structural glasses, , , , and . Nature Communications, (Apr 24, 2014)A note on weakly discontinuous dynamical transitions, , , , and . The Journal of Chemical Physics, 138 (6): 064504+ (Nov 7, 2013)Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 4333-4342. PMLR, (2019)Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference., , , , , and . CoRR, (2018)