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Learning curves for deep structured Gaussian feature models
v1v2v3 (latest)

Learning curves for deep structured Gaussian feature models

Neural Information Processing Systems (NeurIPS), 2023
1 March 2023
Jacob A. Zavatone-Veth
Cengiz Pehlevan
    MLT
ArXiv (abs)PDFHTML

Papers citing "Learning curves for deep structured Gaussian feature models"

8 / 8 papers shown
One-Bit Quantization for Random Features Models
One-Bit Quantization for Random Features Models
D. Akhtiamov
Reza Ghane
B. Hassibi
MQ
186
0
0
17 Oct 2025
Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure
Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with StructureInternational Conference on Learning Representations (ICLR), 2025
Samet Demir
Zafer Dogan
MLT
363
4
0
02 Mar 2025
Input-Label Correlation Governs a Linear-to-Nonlinear Transition in Random Features under Spiked Covariance
Input-Label Correlation Governs a Linear-to-Nonlinear Transition in Random Features under Spiked Covariance
Samet Demir
Zafer Dogan
268
4
0
30 Sep 2024
How Feature Learning Can Improve Neural Scaling Laws
How Feature Learning Can Improve Neural Scaling LawsInternational Conference on Learning Representations (ICLR), 2024
Blake Bordelon
Alexander B. Atanasov
Cengiz Pehlevan
531
43
0
26 Sep 2024
Risk and cross validation in ridge regression with correlated samples
Risk and cross validation in ridge regression with correlated samples
Alexander B. Atanasov
Jacob A. Zavatone-Veth
Cengiz Pehlevan
571
8
0
08 Aug 2024
Asymptotics of Learning with Deep Structured (Random) Features
Asymptotics of Learning with Deep Structured (Random) Features
Dominik Schröder
Daniil Dmitriev
Hugo Cui
Bruno Loureiro
313
12
0
21 Feb 2024
Asymptotics of feature learning in two-layer networks after one
  gradient-step
Asymptotics of feature learning in two-layer networks after one gradient-step
Hugo Cui
Luca Pesce
Yatin Dandi
Florent Krzakala
Yue M. Lu
Lenka Zdeborová
Bruno Loureiro
MLT
350
28
0
07 Feb 2024
More is Better in Modern Machine Learning: when Infinite
  Overparameterization is Optimal and Overfitting is Obligatory
More is Better in Modern Machine Learning: when Infinite Overparameterization is Optimal and Overfitting is Obligatory
James B. Simon
Dhruva Karkada
Nikhil Ghosh
Mikhail Belkin
AI4CEBDL
533
22
0
24 Nov 2023
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