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Modelling the influence of data structure on learning in neural networks: the hidden manifold model

, , , and . (2019)cite arxiv:1909.11500.

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Learning Gaussian Mixtures with Generalized Linear Models: Precise Asymptotics in High-dimensions., , , , , and . NeurIPS, page 10144-10157. (2021)Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime., , , and . NeurIPS, page 10131-10143. (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)Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime., , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 2280-2290. PMLR, (2020)Bayes-optimal Learning of Deep Random Networks of Extensive-width., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 6468-6521. PMLR, (2023)Are Gaussian Data All You Need? The Extents and Limits of Universality in High-Dimensional Generalized Linear Estimation., , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 27680-27708. PMLR, (2023)Performance Limits for Noisy Multimeasurement Vector Problems., , and . IEEE Trans. Signal Process., 65 (9): 2444-2454 (2017)Approximate Message-Passing Decoder and Capacity Achieving Sparse Superposition Codes., and . IEEE Trans. Inf. Theory, 63 (8): 4894-4927 (2017)Who is Afraid of Big Bad Minima? Analysis of Gradient-Flow in a Spiked Matrix-Tensor Model., , , , and . CoRR, (2019)Clustering from sparse pairwise measurements., , , and . ISIT, page 780-784. IEEE, (2016)