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To understand deep learning we need to understand kernel learning

5 February 2018

Papers citing "To understand deep learning we need to understand kernel learning"

50 / 271 papers shown

Title
On Emergence of Clean-Priority Learning in Early Stopped Neural Networks Chaoyue Liu Amirhesam Abedsoltan M. Belkin NoLa 63 5 0 05 Jun 2023
From Tempered to Benign Overfitting in ReLU Neural Networks Guy Kornowski Gilad Yehudai Ohad Shamir 91 13 0 24 May 2023
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension Moritz Haas David Holzmüller U. V. Luxburg Ingo Steinwart MLT 102 14 0 23 May 2023
Prediction Risk and Estimation Risk of the Ridgeless Least Squares Estimator under General Assumptions on Regression Errors Sungyoon Lee S. Lee 43 0 0 22 May 2023
On the ISS Property of the Gradient Flow for Single Hidden-Layer Neural Networks with Linear Activations A. C. B. D. Oliveira Milad Siami Eduardo Sontag 110 2 0 17 May 2023
ChatGPT-Like Large-Scale Foundation Models for Prognostics and Health Management: A Survey and Roadmaps Yanfang Li Huan Wang Muxia Sun LM&MA AI4TS AI4CE 103 59 0 10 May 2023
Approximation by non-symmetric networks for cross-domain learning H. Mhaskar 79 1 0 06 May 2023
New Equivalences Between Interpolation and SVMs: Kernels and Structured Features Chiraag Kaushik Andrew D. McRae Mark A. Davenport Vidya Muthukumar 94 2 0 03 May 2023
Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control Jann Spiess Guido Imbens A. Venugopal CML 76 8 0 01 May 2023
Understanding Overfitting in Adversarial Training via Kernel Regression Teng Zhang Kang Li 56 2 0 13 Apr 2023
Deep neural networks have an inbuilt Occam's razor Chris Mingard Henry Rees Guillermo Valle Pérez A. Louis UQCV BDL 62 16 0 13 Apr 2023
Towards Understanding How Data Augmentation Works with Imbalanced Data Damien Dablain Nitesh Chawla AI4CE 65 2 0 12 Apr 2023
Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning Peizhong Ju Yitao Liang Ness B. Shroff MLT AI4CE 62 3 0 09 Apr 2023
On Mitigating the Utility-Loss in Differentially Private Learning: A new Perspective by a Geometrically Inspired Kernel Approach Mohit Kumar Bernhard A. Moser Lukas Fischer 73 3 0 03 Apr 2023
On Feature Scaling of Recursive Feature Machines Arunav Gupta Rohit Mishra William Luu Mehdi Bouassami 29 1 0 28 Mar 2023
Benign Overfitting for Two-layer ReLU Convolutional Neural Networks Yiwen Kou Zi-Yuan Chen Yuanzhou Chen Quanquan Gu MLT 94 17 0 07 Mar 2023
On Statistical Properties of Sharpness-Aware Minimization: Provable Guarantees Kayhan Behdin Rahul Mazumder 127 6 0 23 Feb 2023
$Generalization Ability of Wide Neural Networks on $\mathbb{R}$$ Generalization Ability of Wide Neural Networks on $\mathbb{R}$ Jianfa Lai Manyun Xu Rui Chen Qi-Rong Lin 84 23 0 12 Feb 2023
Theory on Forgetting and Generalization of Continual Learning Sen Lin Peizhong Ju Yitao Liang Ness B. Shroff CLL 88 47 0 12 Feb 2023
Unsupervised Neighborhood Propagation Kernel Layers for Semi-supervised Node Classification Sonny Achten F. Tonin Panagiotis Patrinos Johan A. K. Suykens 90 4 0 31 Jan 2023
Deep networks for system identification: a Survey G. Pillonetto Aleksandr Aravkin Daniel Gedon L. Ljung Antônio H. Ribeiro Thomas B. Schon OOD 105 45 0 30 Jan 2023
Supervision Complexity and its Role in Knowledge Distillation Hrayr Harutyunyan A. S. Rawat A. Menon Seungyeon Kim Surinder Kumar 92 12 0 28 Jan 2023
A Simple Algorithm For Scaling Up Kernel Methods Tengyu Xu Bryan Kelly Semyon Malamud 64 0 0 26 Jan 2023
A Data-Adaptive Prior for Bayesian Learning of Kernels in Operators Neil K. Chada Quanjun Lang Fei Lu Xiang Wang 69 3 0 29 Dec 2022
T-SEA: Transfer-based Self-Ensemble Attack on Object Detection Hao Huang Ziyan Chen Huanran Chen Yongtao Wang Ke-Yue Zhang AAML 110 59 0 16 Nov 2022
Spectral Evolution and Invariance in Linear-width Neural Networks Zhichao Wang A. Engel Anand D. Sarwate Ioana Dumitriu Tony Chiang 116 18 0 11 Nov 2022
Transfer Learning with Kernel Methods Adityanarayanan Radhakrishnan Max Ruiz Luyten Neha Prasad Caroline Uhler 52 25 0 01 Nov 2022
Learning Ability of Interpolating Deep Convolutional Neural Networks Tiancong Zhou X. Huo AI4CE 99 13 0 25 Oct 2022
Deep Neural Networks as the Semi-classical Limit of Topological Quantum Neural Networks: The problem of generalisation A. Marcianò De-Wei Chen Filippo Fabrocini C. Fields M. Lulli Emanuele Zappala GNN 37 5 0 25 Oct 2022
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes Liam Hodgkinson Christopher van der Heide Fred Roosta Michael W. Mahoney UQCV 79 6 0 14 Oct 2022
Block-wise Training of Residual Networks via the Minimizing Movement Scheme Skander Karkar Ibrahim Ayed Emmanuel de Bézenac Patrick Gallinari 68 1 0 03 Oct 2022
On the Impossible Safety of Large AI Models El-Mahdi El-Mhamdi Sadegh Farhadkhani R. Guerraoui Nirupam Gupta L. Hoang Rafael Pinot Sébastien Rouault John Stephan 110 33 0 30 Sep 2022
Top-Tuning: a study on transfer learning for an efficient alternative to fine tuning for image classification with fast kernel methods P. D. Alfano Vito Paolo Pastore Lorenzo Rosasco Francesca Odone 49 7 0 16 Sep 2022
Bounding generalization error with input compression: An empirical study with infinite-width networks A. Galloway A. Golubeva Mahmoud Salem Mihai Nica Yani Andrew Ioannou Graham W. Taylor MLT AI4CE 71 4 0 19 Jul 2022
Benign, Tempered, or Catastrophic: A Taxonomy of Overfitting Neil Rohit Mallinar James B. Simon Amirhesam Abedsoltan Parthe Pandit M. Belkin Preetum Nakkiran 104 39 0 14 Jul 2022
Efficient Augmentation for Imbalanced Deep Learning Damien Dablain C. Bellinger Bartosz Krawczyk Nitesh Chawla 66 7 0 13 Jul 2022
Benign overfitting and adaptive nonparametric regression J. Chhor Suzanne Sigalla Alexandre B. Tsybakov 44 3 0 27 Jun 2022
Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence Margalit Glasgow Colin Wei Mary Wootters Tengyu Ma 94 5 0 16 Jun 2022
Generalization for multiclass classification with overparameterized linear models Vignesh Subramanian Rahul Arya A. Sahai AI4CE 73 9 0 03 Jun 2022
Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models Kaiyue Wen Jiaye Teng J.N. Zhang NoLa 48 5 0 01 Jun 2022
VC Theoretical Explanation of Double Descent Eng Hock Lee V. Cherkassky 57 3 0 31 May 2022
A Blessing of Dimensionality in Membership Inference through Regularization Jasper Tan Daniel LeJeune Blake Mason Hamid Javadi Richard G. Baraniuk 82 20 0 27 May 2022
On the Inconsistency of Kernel Ridgeless Regression in Fixed Dimensions Daniel Beaglehole M. Belkin Parthe Pandit 62 11 0 26 May 2022
Bandwidth Selection for Gaussian Kernel Ridge Regression via Jacobian Control Oskar Allerbo Rebecka Jörnsten 69 2 0 24 May 2022
Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime Hong Hu Yue M. Lu 92 16 0 13 May 2022
Ridgeless Regression with Random Features Jian Li Yong-Jin Liu Yingying Zhang 39 2 0 01 May 2022
The Directional Bias Helps Stochastic Gradient Descent to Generalize in Kernel Regression Models Yiling Luo X. Huo Y. Mei 44 0 0 29 Apr 2022
Spectrum of inner-product kernel matrices in the polynomial regime and multiple descent phenomenon in kernel ridge regression Theodor Misiakiewicz 67 40 0 21 Apr 2022
Deep Learning meets Nonparametric Regression: Are Weight-Decayed DNNs Locally Adaptive? Kaiqi Zhang Yu Wang 118 12 0 20 Apr 2022
Concentration of Random Feature Matrices in High-Dimensions Zhijun Chen Hayden Schaeffer Rachel A. Ward 90 6 0 14 Apr 2022