Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks

3 October 2019

Dingli Yu

Papers citing "Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks"

40 / 40 papers shown

Title
Unsupervised Replay Strategies for Continual Learning with Limited Data Anthony Bazhenov Pahan Dewasurendra G. Krishnan Jean Erik Delanois CLL 24 0 0 21 Oct 2024
Neural Lineage Runpeng Yu Xinchao Wang 26 4 0 17 Jun 2024
Deep Continuous Networks Nergis Tomen S. Pintea J. C. V. Gemert 92 14 0 02 Feb 2024
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models Guillermo Ortiz-Jiménez Alessandro Favero P. Frossard MoMe 42 106 0 22 May 2023
Cut your Losses with Squentropy Like Hui M. Belkin S. Wright UQCV 13 8 0 08 Feb 2023
A Simple Algorithm For Scaling Up Kernel Methods Tengyu Xu Bryan T. Kelly Semyon Malamud 11 0 0 26 Jan 2023
Global Convergence of SGD On Two Layer Neural Nets Pulkit Gopalani Anirbit Mukherjee 23 5 0 20 Oct 2022
Why Quantization Improves Generalization: NTK of Binary Weight Neural Networks Kaiqi Zhang Ming Yin Yu-Xiang Wang MQ 16 4 0 13 Jun 2022
Infinite Recommendation Networks: A Data-Centric Approach Noveen Sachdeva Mehak Preet Dhaliwal Carole-Jean Wu Julian McAuley DD 31 28 0 03 Jun 2022
Analyzing Tree Architectures in Ensembles via Neural Tangent Kernel Ryuichi Kanoh M. Sugiyama 23 2 0 25 May 2022
Wide and Deep Neural Networks Achieve Optimality for Classification Adityanarayanan Radhakrishnan M. Belkin Caroline Uhler 16 18 0 29 Apr 2022
Multi-model Ensemble Analysis with Neural Network Gaussian Processes Trevor Harris B. Li Ryan Sriver 22 5 0 08 Feb 2022
Deep Layer-wise Networks Have Closed-Form Weights Chieh-Tsai Wu A. Masoomi A. Gretton Jennifer Dy 29 3 0 01 Feb 2022
Forward Operator Estimation in Generative Models with Kernel Transfer Operators Z. Huang Rudrasis Chakraborty Vikas Singh GAN 14 3 0 01 Dec 2021
On the Effectiveness of Neural Ensembles for Image Classification with Small Datasets Lorenzo Brigato Luca Iocchi UQCV 22 0 0 29 Nov 2021
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
Subquadratic Overparameterization for Shallow Neural Networks Chaehwan Song Ali Ramezani-Kebrya Thomas Pethick Armin Eftekhari V. Cevher 24 32 0 02 Nov 2021
VC dimension of partially quantized neural networks in the overparametrized regime Yutong Wang Clayton D. Scott 14 1 0 06 Oct 2021
How Powerful is Graph Convolution for Recommendation? Yifei Shen Yongji Wu Yao Zhang Caihua Shan Jun Zhang Khaled B. Letaief Dongsheng Li GNN 28 99 0 17 Aug 2021
Dataset Distillation with Infinitely Wide Convolutional Networks Timothy Nguyen Roman Novak Lechao Xiao Jaehoon Lee DD 32 229 0 27 Jul 2021
How to Train Your Wide Neural Network Without Backprop: An Input-Weight Alignment Perspective Akhilan Boopathy Ila Fiete 16 9 0 15 Jun 2021
What can linearized neural networks actually say about generalization? Guillermo Ortiz-Jiménez Seyed-Mohsen Moosavi-Dezfooli P. Frossard 26 43 0 12 Jun 2021
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective Geoff Pleiss John P. Cunningham 26 24 0 11 Jun 2021
A Neural Tangent Kernel Perspective of GANs Jean-Yves Franceschi Emmanuel de Bézenac Ibrahim Ayed Mickaël Chen Sylvain Lamprier Patrick Gallinari 31 26 0 10 Jun 2021
The Future is Log-Gaussian: ResNets and Their Infinite-Depth-and-Width Limit at Initialization Mufan Bill Li Mihai Nica Daniel M. Roy 23 33 0 07 Jun 2021
Priors in Bayesian Deep Learning: A Review Vincent Fortuin UQCV BDL 29 124 0 14 May 2021
A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity Seo Taek Kong Soomin Jeon Dongbin Na Jaewon Lee Honglak Lee Kyu-Hwan Jung 17 6 0 08 Apr 2021
Dataset Meta-Learning from Kernel Ridge-Regression Timothy Nguyen Zhourung Chen Jaehoon Lee DD 36 238 0 30 Oct 2020
Multiple Descent: Design Your Own Generalization Curve Lin Chen Yifei Min M. Belkin Amin Karbasi DRL 18 61 0 03 Aug 2020
Tensor Programs II: Neural Tangent Kernel for Any Architecture Greg Yang 40 134 0 25 Jun 2020
On the Preservation of Spatio-temporal Information in Machine Learning Applications Yigit Oktar Mehmet Türkan 8 1 0 15 Jun 2020
To Each Optimizer a Norm, To Each Norm its Generalization Sharan Vaswani Reza Babanezhad Jose Gallego Aaron Mishkin Simon Lacoste-Julien Nicolas Le Roux 24 8 0 11 Jun 2020
Modularizing Deep Learning via Pairwise Learning With Kernels Shiyu Duan Shujian Yu José C. Príncipe MoMe 25 20 0 12 May 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 34 172 0 23 Apr 2020
A Close Look at Deep Learning with Small Data Lorenzo Brigato Luca Iocchi 19 139 0 28 Mar 2020
Double Trouble in Double Descent : Bias and Variance(s) in the Lazy Regime Stéphane dÁscoli Maria Refinetti Giulio Biroli Florent Krzakala 93 152 0 02 Mar 2020
On the infinite width limit of neural networks with a standard parameterization Jascha Narain Sohl-Dickstein Roman Novak S. Schoenholz Jaehoon Lee 19 47 0 21 Jan 2020
Neural Tangents: Fast and Easy Infinite Neural Networks in Python Roman Novak Lechao Xiao Jiri Hron Jaehoon Lee Alexander A. Alemi Jascha Narain Sohl-Dickstein S. Schoenholz 27 224 0 05 Dec 2019
Information in Infinite Ensembles of Infinitely-Wide Neural Networks Ravid Shwartz-Ziv Alexander A. Alemi 19 21 0 20 Nov 2019
Implicit Self-Regularization in Deep Neural Networks: Evidence from Random Matrix Theory and Implications for Learning Charles H. Martin Michael W. Mahoney AI4CE 30 190 0 02 Oct 2018