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Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models.

, , , , and . NeurIPS, page 8676-8686. (2019)

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From Zero to Hero: How local curvature at artless initial conditions leads away from bad minima., , and . CoRR, (2024)Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models., , , , and . NeurIPS, page 8676-8686. (2019)Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference., , , , , and . CoRR, (2018)Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval., , , , , and . NeurIPS, (2020)How to iron out rough landscapes and get optimal performances: Replicated Gradient Descent and its application to tensor PCA., , and . CoRR, (2019)Who Has the Last Word? Understanding How to Sample Online Discussions., , , , and . WWW (Companion Volume), page 390. ACM, (2022)Comparing Dynamics: Deep Neural Networks versus Glassy Systems., , , , , , , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 324-333. PMLR, (2018)Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model., , , , and . CoRR, (2019)Who Has the Last Word? Understanding How to Sample Online Discussions., , , , and . ACM Trans. Web, 15 (3): 12:1-12:25 (2021)Having the Last Word: Understanding How to Sample Discussions Online., , , , and . CoRR, (2019)