Locality defeats the curse of dimensionality in convolutional teacher-student scenarios

16 June 2021

Papers citing "Locality defeats the curse of dimensionality in convolutional teacher-student scenarios"

30 / 30 papers shown

Title
Scaling Laws and Representation Learning in Simple Hierarchical Languages: Transformers vs. Convolutional Architectures Francesco Cagnetta Alessandro Favero Antonio Sclocchi M. Wyart 26 0 0 11 May 2025
Learning curves theory for hierarchically compositional data with power-law distributed features Francesco Cagnetta Hyunmo Kang M. Wyart 36 0 0 11 May 2025
U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models Song Mei 3DV AI4CE DiffM 41 11 0 29 Apr 2024
How Deep Networks Learn Sparse and Hierarchical Data: the Sparse Random Hierarchy Model Umberto M. Tomasini M. Wyart BDL 41 7 0 16 Apr 2024
A Phase Transition in Diffusion Models Reveals the Hierarchical Nature of Data Antonio Sclocchi Alessandro Favero M. Wyart DiffM 41 26 0 26 Feb 2024
Local Kernel Renormalization as a mechanism for feature learning in overparametrized Convolutional Neural Networks R. Aiudi R. Pacelli A. Vezzani R. Burioni P. Rotondo MLT 21 15 0 21 Jul 2023
Kernels, Data & Physics Francesco Cagnetta Deborah Oliveira Mahalakshmi Sabanayagam Nikolaos Tsilivis Julia Kempe 25 0 0 05 Jul 2023
How Deep Neural Networks Learn Compositional Data: The Random Hierarchy Model Francesco Cagnetta Leonardo Petrini Umberto M. Tomasini Alessandro Favero M. Wyart BDL 30 22 0 05 Jul 2023
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
Mapping of attention mechanisms to a generalized Potts model Riccardo Rende Federica Gerace A. Laio Sebastian Goldt 15 22 0 14 Apr 2023
Short-Term Memory Convolutions Grzegorz Stefański Krzysztof Arendt P. Daniluk Bartlomiej Jasik Artur Szumaczuk 14 4 0 08 Feb 2023
The SSL Interplay: Augmentations, Inductive Bias, and Generalization Vivien A. Cabannes B. Kiani Randall Balestriero Yann LeCun A. Bietti SSL 11 31 0 06 Feb 2023
Strong inductive biases provably prevent harmless interpolation Michael Aerni Marco Milanta Konstantin Donhauser Fanny Yang 30 9 0 18 Jan 2023
A Kernel Perspective of Skip Connections in Convolutional Networks Daniel Barzilai Amnon Geifman Meirav Galun Ronen Basri 17 11 0 27 Nov 2022
On the Universal Approximation Property of Deep Fully Convolutional Neural Networks Ting-Wei Lin Zuowei Shen Qianxiao Li 31 4 0 25 Nov 2022
What Can Be Learnt With Wide Convolutional Neural Networks? Francesco Cagnetta Alessandro Favero M. Wyart MLT 38 11 0 01 Aug 2022
Synergy and Symmetry in Deep Learning: Interactions between the Data, Model, and Inference Algorithm Lechao Xiao Jeffrey Pennington 32 10 0 11 Jul 2022
The impact of memory on learning sequence-to-sequence tasks Alireza Seif S. Loos Gennaro Tucci É. Roldán Sebastian Goldt 23 4 0 29 May 2022
Inference of a Rumor's Source in the Independent Cascade Model Petra Berenbrink Max Hahn-Klimroth Dominik Kaaser Lena Krieg M. Rau LRM 11 5 0 24 May 2022
CNNs Avoid Curse of Dimensionality by Learning on Patches Vamshi C. Madala S. Chandrasekaran Jason Bunk UQCV 27 5 0 22 May 2022
On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels Amnon Geifman Meirav Galun David Jacobs Ronen Basri 27 13 0 17 Mar 2022
Data-driven emergence of convolutional structure in neural networks Alessandro Ingrosso Sebastian Goldt 50 38 0 01 Feb 2022
Eigenspace Restructuring: a Principle of Space and Frequency in Neural Networks Lechao Xiao 28 21 0 10 Dec 2021
Learning Curves for Continual Learning in Neural Networks: Self-Knowledge Transfer and Forgetting Ryo Karakida S. Akaho CLL 24 11 0 03 Dec 2021
Learning with convolution and pooling operations in kernel methods Theodor Misiakiewicz Song Mei MLT 15 29 0 16 Nov 2021
On the Sample Complexity of Learning under Invariance and Geometric Stability A. Bietti Luca Venturi Joan Bruna 27 5 0 14 Jun 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 46 89 0 25 Feb 2021
Approximation and Learning with Deep Convolutional Models: a Kernel Perspective A. Bietti 29 29 0 19 Feb 2021
Towards Learning Convolutions from Scratch Behnam Neyshabur SSL 220 71 0 27 Jul 2020
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks Blake Bordelon Abdulkadir Canatar C. Pehlevan 139 201 0 07 Feb 2020