Early-stopped neural networks are consistent

10 June 2021

Papers citing "Early-stopped neural networks are consistent"

9 / 9 papers shown

Title
EdgeSync: Faster Edge-model Updating via Adaptive Continuous Learning for Video Data Drift Peng Zhao Runchu Dong Guiqin Wang Cong Zhao 40 1 0 05 Jun 2024
Connecting NTK and NNGP: A Unified Theoretical Framework for Wide Neural Network Learning Dynamics Yehonatan Avidan Qianyi Li H. Sompolinsky 60 8 0 08 Sep 2023
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension Moritz Haas David Holzmüller U. V. Luxburg Ingo Steinwart MLT 37 14 0 23 May 2023
Automatic Data Augmentation via Invariance-Constrained Learning Ignacio Hounie Luiz F. O. Chamon Alejandro Ribeiro 26 10 0 29 Sep 2022
Benign, Tempered, or Catastrophic: A Taxonomy of Overfitting Neil Rohit Mallinar James B. Simon Amirhesam Abedsoltan Parthe Pandit M. Belkin Preetum Nakkiran 26 37 0 14 Jul 2022
The Spectral Bias of Polynomial Neural Networks Moulik Choraria L. Dadi Grigorios G. Chrysos Julien Mairal V. Cevher 24 18 0 27 Feb 2022
Random Feature Amplification: Feature Learning and Generalization in Neural Networks Spencer Frei Niladri S. Chatterji Peter L. Bartlett MLT 30 29 0 15 Feb 2022
Agnostic Learnability of Halfspaces via Logistic Loss Ziwei Ji Kwangjun Ahn Pranjal Awasthi Satyen Kale Stefani Karp 8 3 0 31 Jan 2022
Achieving Small Test Error in Mildly Overparameterized Neural Networks Shiyu Liang Ruoyu Sun R. Srikant 20 3 0 24 Apr 2021