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SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics


Feb 21, 2023
Emmanuel Abbe, Enric Boix-Adsera, Theodor Misiakiewicz

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Generalization on the Unseen, Logic Reasoning and Degree Curriculum


Jan 30, 2023
Emmanuel Abbe, Samy Bengio, Aryo Lotfi, Kevin Rizk

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* 37 pages, 10 figures 

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On the non-universality of deep learning: quantifying the cost of symmetry


Aug 05, 2022
Emmanuel Abbe, Enric Boix-Adsera

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Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures


May 26, 2022
Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon Kleinberg, Aryo Lotfi, Maithra Raghu, Chiyuan Zhang

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* 28 pages, 8 figures 

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An initial alignment between neural network and target is needed for gradient descent to learn


Feb 25, 2022
Emmanuel Abbe, Elisabetta Cornacchia, Jan HΔ…zΕ‚a, Christopher Marquis

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The merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks


Feb 17, 2022
Emmanuel Abbe, Enric Boix-Adsera, Theodor Misiakiewicz

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Binary perceptron: efficient algorithms can find solutions in a rare well-connected cluster


Nov 04, 2021
Emmanuel Abbe, Shuangping Li, Allan Sly

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The staircase property: How hierarchical structure can guide deep learning


Aug 24, 2021
Emmanuel Abbe, Enric Boix-Adsera, Matthew Brennan, Guy Bresler, Dheeraj Nagaraj

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On the Power of Differentiable Learning versus PAC and SQ Learning


Aug 09, 2021
Emmanuel Abbe, Pritish Kamath, Eran Malach, Colin Sandon, Nathan Srebro

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Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels


Mar 01, 2021
Eran Malach, Pritish Kamath, Emmanuel Abbe, Nathan Srebro

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