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On the information bottleneck theory of deep learning, , , , , , and . Journal of Statistical Mechanics: Theory and Experiment, 2019 (12): 124020 (December 2019)On the Information Bottleneck Theory of Deep Learning., , , , , , and . ICLR (Poster), OpenReview.net, (2018)On the information bottleneck theory of deep learning, , , and . (2018)A new role for circuit expansion for learning in neural networks., , and . CoRR, (2020)An equivalence between high dimensional Bayes optimal inference and M-estimation., and . NIPS, page 3378-3386. (2016)Dimensionality compression and expansion in Deep Neural Networks., , , , , and . CoRR, (2019)Minnorm training: an algorithm for training over-parameterized deep neural networks., , , and . CoRR, (2018)Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup., , , , and . NeurIPS, page 6979-6989. (2019)Statistical mechanics of complex neural systems and high dimensional data, , and . Journal of Statistical Mechanics: Theory and Experiment, 2013 (03): P03014+ (Jan 30, 2013)Energy-entropy competition and the effectiveness of stochastic gradient descent in machine learning., , , and . CoRR, (2018)