The Interpolation Phase Transition in Neural Networks: Memorization and Generalization under Lazy Training

25 July 2020

Papers citing "The Interpolation Phase Transition in Neural Networks: Memorization and Generalization under Lazy Training"

24 / 74 papers shown

Title
A Framework for Overparameterized Learning Dávid Terjék Diego González-Sánchez MLT 11 1 0 26 May 2022
Quadratic models for understanding catapult dynamics of neural networks Libin Zhu Chaoyue Liu Adityanarayanan Radhakrishnan M. Belkin 27 13 0 24 May 2022
Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture Libin Zhu Chaoyue Liu M. Belkin GNN AI4CE 15 4 0 24 May 2022
Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization Simone Bombari Mohammad Hossein Amani Marco Mondelli 20 26 0 20 May 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation Jimmy Ba Murat A. Erdogdu Taiji Suzuki Zhichao Wang Denny Wu Greg Yang MLT 31 121 0 03 May 2022
Adversarial Examples in Random Neural Networks with General Activations Andrea Montanari Yuchen Wu GAN AAML 74 13 0 31 Mar 2022
An Empirical Study of Memorization in NLP Xiaosen Zheng Jing Jiang TDI 17 24 1 23 Mar 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes Elvis Dohmatob A. Bietti AAML 21 13 0 22 Mar 2022
Universality of empirical risk minimization Andrea Montanari Basil Saeed OOD 25 73 0 17 Feb 2022
Benign Overfitting in Two-layer Convolutional Neural Networks Yuan Cao Zixiang Chen M. Belkin Quanquan Gu MLT 19 82 0 14 Feb 2022
Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data Spencer Frei Niladri S. Chatterji Peter L. Bartlett MLT 34 69 0 11 Feb 2022
Deformed semicircle law and concentration of nonlinear random matrices for ultra-wide neural networks Zhichao Wang Yizhe Zhu 25 18 0 20 Sep 2021
Deep Networks Provably Classify Data on Curves Tingran Wang Sam Buchanan D. Gilboa John N. Wright 23 9 0 29 Jul 2021
Nonasymptotic theory for two-layer neural networks: Beyond the bias-variance trade-off Huiyuan Wang Wei Lin MLT 24 4 0 09 Jun 2021
Fundamental tradeoffs between memorization and robustness in random features and neural tangent regimes Elvis Dohmatob 19 9 0 04 Jun 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features Zhihui Zhu Tianyu Ding Jinxin Zhou Xiao Li Chong You Jeremias Sulam Qing Qu 16 195 0 06 May 2021
Risk Bounds for Over-parameterized Maximum Margin Classification on Sub-Gaussian Mixtures Yuan Cao Quanquan Gu M. Belkin 4 51 0 28 Apr 2021
A Recipe for Global Convergence Guarantee in Deep Neural Networks Kenji Kawaguchi Qingyun Sun 16 11 0 12 Apr 2021
When Are Solutions Connected in Deep Networks? Quynh N. Nguyen Pierre Bréchet Marco Mondelli 22 9 0 18 Feb 2021
On the Theory of Implicit Deep Learning: Global Convergence with Implicit Layers Kenji Kawaguchi PINN 20 41 0 15 Feb 2021
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks Quynh N. Nguyen Marco Mondelli Guido Montúfar 22 81 0 21 Dec 2020
Benign overfitting in ridge regression Alexander Tsigler Peter L. Bartlett 23 159 0 29 Sep 2020
Deep Networks and the Multiple Manifold Problem Sam Buchanan D. Gilboa John N. Wright 166 39 0 25 Aug 2020
Large-time asymptotics in deep learning Carlos Esteve Borjan Geshkovski Dario Pighin Enrique Zuazua 14 34 0 06 Aug 2020