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SGD Finds then Tunes Features in Two-Layer Neural Networks with
  near-Optimal Sample Complexity: A Case Study in the XOR problem
v1v2 (latest)

SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem

International Conference on Learning Representations (ICLR), 2023
26 September 2023
Margalit Glasgow
    MLT
ArXiv (abs)PDFHTML

Papers citing "SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem"

16 / 16 papers shown
Title
A Derandomization Framework for Structure Discovery: Applications in Neural Networks and Beyond
A Derandomization Framework for Structure Discovery: Applications in Neural Networks and Beyond
Nikos Tsikouras
Yorgos Pantis
Ioannis Mitliagkas
Christos Tzamos
BDL
142
0
0
22 Oct 2025
How Does Label Noise Gradient Descent Improve Generalization in the Low SNR Regime?
How Does Label Noise Gradient Descent Improve Generalization in the Low SNR Regime?
Wei Huang
Andi Han
Yujin Song
Yilan Chen
Denny Wu
Difan Zou
Taiji Suzuki
NoLaMLT
166
0
0
20 Oct 2025
Mamba Can Learn Low-Dimensional Targets In-Context via Test-Time Feature Learning
Mamba Can Learn Low-Dimensional Targets In-Context via Test-Time Feature Learning
Junsoo Oh
Wei Huang
Taiji Suzuki
176
0
0
14 Oct 2025
HoloScene: Simulation-Ready Interactive 3D Worlds from a Single Video
HoloScene: Simulation-Ready Interactive 3D Worlds from a Single Video
Hongchi Xia
Chih-Hao Lin
Hao-Yu Hsu
Quentin Leboutet
Katelyn Gao
Michael Paulitsch
Benjamin Ummenhofer
Shenlong Wang
VGen
100
0
0
07 Oct 2025
Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks
Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks
D. Kunin
Giovanni Luca Marchetti
F. Chen
Dhruva Karkada
James B. Simon
M. DeWeese
Surya Ganguli
Nina Miolane
313
3
0
06 Jun 2025
Survey on Algorithms for multi-index models
Survey on Algorithms for multi-index modelsStatistical Science (Stat. Sci.), 2025
Joan Bruna
Daniel Hsu
268
9
0
07 Apr 2025
Learning a Single Index Model from Anisotropic Data with vanilla Stochastic Gradient Descent
Learning a Single Index Model from Anisotropic Data with vanilla Stochastic Gradient DescentInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Guillaume Braun
Minh Ha Quang
Masaaki Imaizumi
MLT
207
3
0
31 Mar 2025
Convergence of Shallow ReLU Networks on Weakly Interacting Data
Convergence of Shallow ReLU Networks on Weakly Interacting Data
Léo Dana
Francis R. Bach
Loucas Pillaud-Vivien
MLT
241
2
0
24 Feb 2025
Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional Convergence
Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional ConvergenceInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Berfin Simsek
Amire Bendjeddou
Daniel Hsu
345
4
0
13 Nov 2024
Robust Feature Learning for Multi-Index Models in High Dimensions
Robust Feature Learning for Multi-Index Models in High DimensionsInternational Conference on Learning Representations (ICLR), 2024
Alireza Mousavi-Hosseini
Adel Javanmard
Murat A. Erdogdu
OODAAML
446
5
0
21 Oct 2024
Shallow diffusion networks provably learn hidden low-dimensional
  structure
Shallow diffusion networks provably learn hidden low-dimensional structure
Nicholas M. Boffi
Arthur Jacot
Stephen Tu
Ingvar M. Ziemann
DiffM
202
5
0
15 Oct 2024
Sharper Guarantees for Learning Neural Network Classifiers with Gradient
  Methods
Sharper Guarantees for Learning Neural Network Classifiers with Gradient MethodsInternational Conference on Learning Representations (ICLR), 2024
Hossein Taheri
Christos Thrampoulidis
Arya Mazumdar
MLT
295
2
0
13 Oct 2024
On the Complexity of Learning Sparse Functions with Statistical and
  Gradient Queries
On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
Nirmit Joshi
Theodor Misiakiewicz
Nathan Srebro
187
10
0
08 Jul 2024
Neural network learns low-dimensional polynomials with SGD near the
  information-theoretic limit
Neural network learns low-dimensional polynomials with SGD near the information-theoretic limit
Jason D. Lee
Kazusato Oko
Taiji Suzuki
Denny Wu
MLT
308
31
0
03 Jun 2024
Matching the Statistical Query Lower Bound for k-sparse Parity Problems
  with Stochastic Gradient Descent
Matching the Statistical Query Lower Bound for k-sparse Parity Problems with Stochastic Gradient Descent
Yiwen Kou
Zixiang Chen
Quanquan Gu
Sham Kakade
192
2
0
18 Apr 2024
Complexity Matters: Dynamics of Feature Learning in the Presence of
  Spurious Correlations
Complexity Matters: Dynamics of Feature Learning in the Presence of Spurious Correlations
GuanWen Qiu
Da Kuang
Surbhi Goel
388
11
0
05 Mar 2024
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