Every Model Learned by Gradient Descent Is Approximately a Kernel Machine

30 November 2020

Papers citing "Every Model Learned by Gradient Descent Is Approximately a Kernel Machine"

14 / 14 papers shown

Title
Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations Andrzej Perzanowski Tony Lindeberg 45 1 0 17 Sep 2024
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo Ramin Hasani Alexander Amini Daniela Rus AAML 28 12 0 21 Oct 2022
On the optimization and generalization of overparameterized implicit neural networks Tianxiang Gao Hongyang Gao MLT AI4CE 19 3 0 30 Sep 2022
Interpretable (not just posthoc-explainable) medical claims modeling for discharge placement to prevent avoidable all-cause readmissions or death Joshua C. Chang Ted L. Chang Carson C. Chow R. Mahajan Sonya Mahajan Joe Maisog Shashaank Vattikuti Hongjing Xia FAtt OOD 27 0 0 28 Aug 2022
Efficient Augmentation for Imbalanced Deep Learning Damien Dablain C. Bellinger Bartosz Krawczyk Nitesh V. Chawla 22 7 0 13 Jul 2022
A Survey of Automated Data Augmentation Algorithms for Deep Learning-based Image Classification Tasks Z. Yang Richard Sinnott James Bailey Qiuhong Ke 16 39 0 14 Jun 2022
On the Equivalence between Neural Network and Support Vector Machine Yilan Chen Wei Huang Lam M. Nguyen Tsui-Wei Weng AAML 17 18 0 11 Nov 2021
Neural Networks as Kernel Learners: The Silent Alignment Effect Alexander B. Atanasov Blake Bordelon C. Pehlevan MLT 13 74 0 29 Oct 2021
New Insights into Graph Convolutional Networks using Neural Tangent Kernels Mahalakshmi Sabanayagam P. Esser D. Ghoshdastidar 21 6 0 08 Oct 2021
Associative Memories via Predictive Coding Tommaso Salvatori Yuhang Song Yujian Hong Simon Frieder Lei Sha Zhenghua Xu Rafal Bogacz Thomas Lukasiewicz 16 61 0 16 Sep 2021
PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them Patrick Lewis Yuxiang Wu Linqing Liu Pasquale Minervini Heinrich Küttler Aleksandra Piktus Pontus Stenetorp Sebastian Riedel RALM 23 228 0 13 Feb 2021
Data-driven geophysical forecasting: Simple, low-cost, and accurate baselines with kernel methods B. Hamzi R. Maulik H. Owhadi AI4TS 9 28 0 13 Feb 2021
Online Limited Memory Neural-Linear Bandits with Likelihood Matching Ofir Nabati Tom Zahavy Shie Mannor 19 18 0 07 Feb 2021
AdaSwarm: Augmenting Gradient-Based optimizers in Deep Learning with Swarm Intelligence Rohan Mohapatra Snehanshu Saha C. Coello Anwesh Bhattacharya S. Dhavala S. Saha ODL 13 21 0 19 May 2020