Characterizing the Spectrum of the NTK via a Power Series Expansion

15 November 2022

Papers citing "Characterizing the Spectrum of the NTK via a Power Series Expansion"

10 / 10 papers shown

Title
Variational Search Distributions Daniel M. Steinberg Rafael Oliveira Cheng Soon Ong Edwin V. Bonilla 30 0 0 10 Sep 2024
Parameter-Efficient Fine-Tuning for Continual Learning: A Neural Tangent Kernel Perspective Jingren Liu Zhong Ji Yunlong Yu Jiale Cao Yanwei Pang Jungong Han Xuelong Li CLL 29 3 0 24 Jul 2024
Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension Kedar Karhadkar Michael Murray Guido Montúfar 22 2 0 23 May 2024
NTK-Guided Few-Shot Class Incremental Learning Jingren Liu Zhong Ji Yanwei Pang Yunlong Yu CLL 27 3 0 19 Mar 2024
Near-Interpolators: Rapid Norm Growth and the Trade-Off between Interpolation and Generalization Yutong Wang Rishi Sonthalia Wei Hu 27 2 0 12 Mar 2024
A note on regularised NTK dynamics with an application to PAC-Bayesian training Eugenio Clerico Benjamin Guedj 15 0 0 20 Dec 2023
Controlling the Inductive Bias of Wide Neural Networks by Modifying the Kernel's Spectrum Amnon Geifman Daniel Barzilai Ronen Basri Meirav Galun 14 4 0 26 Jul 2023
Overparameterized random feature regression with nearly orthogonal data Zhichao Wang Yizhe Zhu 10 3 0 11 Nov 2022
Fast Neural Kernel Embeddings for General Activations Insu Han A. Zandieh Jaehoon Lee Roman Novak Lechao Xiao Amin Karbasi 41 17 0 09 Sep 2022
On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths Quynh N. Nguyen 25 49 0 24 Jan 2021