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2001.05205
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Learning a Single Neuron with Gradient Methods
Annual Conference Computational Learning Theory (COLT), 2020
15 January 2020
Gilad Yehudai
Ohad Shamir
MLT
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Papers citing
"Learning a Single Neuron with Gradient Methods"
48 / 48 papers shown
Gradient descent for deep equilibrium single-index models
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A Derandomization Framework for Structure Discovery: Applications in Neural Networks and Beyond
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Yorgos Pantis
Ioannis Mitliagkas
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210
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Low-dimensional Functions are Efficiently Learnable under Randomly Biased Distributions
Annual Conference Computational Learning Theory (COLT), 2025
Elisabetta Cornacchia
Dan Mikulincer
Elchanan Mossel
447
6
0
10 Feb 2025
Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise
Neural Information Processing Systems (NeurIPS), 2024
Shuyao Li
Sushrut Karmalkar
Ilias Diakonikolas
Jelena Diakonikolas
OOD
274
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0
11 Nov 2024
Online Non-Stationary Stochastic Quasar-Convex Optimization
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Iman Shames
220
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04 Jul 2024
Disentangle Sample Size and Initialization Effect on Perfect Generalization for Single-Neuron Target
Jiajie Zhao
Zhiwei Bai
Yaoyu Zhang
342
1
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22 May 2024
Bayesian Inference for Consistent Predictions in Overparameterized Nonlinear Regression
Tomoya Wakayama
BDL
365
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0
06 Apr 2024
Masks, Signs, And Learning Rate Rewinding
Advait Gadhikar
R. Burkholz
281
15
0
29 Feb 2024
RedEx: Beyond Fixed Representation Methods via Convex Optimization
International Conference on Algorithmic Learning Theory (ALT), 2024
Amit Daniely
Mariano Schain
Gilad Yehudai
245
1
0
15 Jan 2024
The Local Landscape of Phase Retrieval Under Limited Samples
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2023
Kaizhao Liu
Zihao Wang
Lei Wu
297
3
0
26 Nov 2023
Should Under-parameterized Student Networks Copy or Average Teacher Weights?
Neural Information Processing Systems (NeurIPS), 2023
Berfin Simsek
Amire Bendjeddou
W. Gerstner
Johanni Brea
362
10
0
03 Nov 2023
Symmetric Single Index Learning
International Conference on Learning Representations (ICLR), 2023
Aaron Zweig
Joan Bruna
MLT
272
4
0
03 Oct 2023
Distribution-Independent Regression for Generalized Linear Models with Oblivious Corruptions
Annual Conference Computational Learning Theory (COLT), 2023
Ilias Diakonikolas
Sushrut Karmalkar
Jongho Park
Christos Tzamos
397
2
0
20 Sep 2023
Gradient-Based Feature Learning under Structured Data
Neural Information Processing Systems (NeurIPS), 2023
Alireza Mousavi-Hosseini
Denny Wu
Taiji Suzuki
Murat A. Erdogdu
MLT
356
29
0
07 Sep 2023
Max-affine regression via first-order methods
SIAM Journal on Mathematics of Data Science (SIMODS), 2023
Seonho Kim
Kiryung Lee
222
3
0
15 Aug 2023
The Effect of SGD Batch Size on Autoencoder Learning: Sparsity, Sharpness, and Feature Learning
Nikhil Ghosh
Spencer Frei
Wooseok Ha
Ting Yu
MLT
329
5
0
06 Aug 2023
On Single Index Models beyond Gaussian Data
Neural Information Processing Systems (NeurIPS), 2023
Joan Bruna
Loucas Pillaud-Vivien
Aaron Zweig
302
15
0
28 Jul 2023
Robustly Learning a Single Neuron via Sharpness
International Conference on Machine Learning (ICML), 2023
Puqian Wang
Nikos Zarifis
Ilias Diakonikolas
Jelena Diakonikolas
207
14
0
13 Jun 2023
Learning a Neuron by a Shallow ReLU Network: Dynamics and Implicit Bias for Correlated Inputs
Neural Information Processing Systems (NeurIPS), 2023
D. Chistikov
Matthias Englert
R. Lazic
MLT
322
16
0
10 Jun 2023
Expand-and-Cluster: Parameter Recovery of Neural Networks
International Conference on Machine Learning (ICML), 2023
Flavio Martinelli
Berfin Simsek
W. Gerstner
Johanni Brea
616
15
0
25 Apr 2023
Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron
International Conference on Machine Learning (ICML), 2023
Jingfeng Wu
Difan Zou
Zixiang Chen
Vladimir Braverman
Quanquan Gu
Sham Kakade
321
9
0
03 Mar 2023
Over-Parameterization Exponentially Slows Down Gradient Descent for Learning a Single Neuron
Annual Conference Computational Learning Theory (COLT), 2023
Weihang Xu
S. Du
429
22
0
20 Feb 2023
Continuized Acceleration for Quasar Convex Functions in Non-Convex Optimization
International Conference on Learning Representations (ICLR), 2023
Jun-Kun Wang
Andre Wibisono
252
20
0
15 Feb 2023
Active Learning for Single Neuron Models with Lipschitz Non-Linearities
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Aarshvi Gajjar
Chinmay Hegde
Christopher Musco
478
13
0
24 Oct 2022
SQ Lower Bounds for Learning Single Neurons with Massart Noise
Neural Information Processing Systems (NeurIPS), 2022
Ilias Diakonikolas
D. Kane
Lisheng Ren
Yuxin Sun
161
8
0
18 Oct 2022
Magnitude and Angle Dynamics in Training Single ReLU Neurons
Neural Networks (NN), 2022
Sangmin Lee
Byeongsu Sim
Jong Chul Ye
MLT
411
6
0
27 Sep 2022
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit
Neural Information Processing Systems (NeurIPS), 2022
Boaz Barak
Benjamin L. Edelman
Surbhi Goel
Sham Kakade
Eran Malach
Cyril Zhang
470
173
0
18 Jul 2022
Learning a Single Neuron with Adversarial Label Noise via Gradient Descent
Annual Conference Computational Learning Theory (COLT), 2022
Ilias Diakonikolas
Vasilis Kontonis
Christos Tzamos
Nikos Zarifis
MLT
219
24
0
17 Jun 2022
Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel Methods
International Conference on Learning Representations (ICLR), 2022
Shunta Akiyama
Taiji Suzuki
337
9
0
30 May 2022
Learning a Single Neuron for Non-monotonic Activation Functions
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Lei Wu
MLT
218
17
0
16 Feb 2022
Random Feature Amplification: Feature Learning and Generalization in Neural Networks
Journal of machine learning research (JMLR), 2022
Spencer Frei
Niladri S. Chatterji
Peter L. Bartlett
MLT
345
36
0
15 Feb 2022
Optimization-Based Separations for Neural Networks
Annual Conference Computational Learning Theory (COLT), 2021
Itay Safran
Jason D. Lee
779
19
0
04 Dec 2021
ReLU Regression with Massart Noise
Neural Information Processing Systems (NeurIPS), 2021
Ilias Diakonikolas
Jongho Park
Christos Tzamos
288
13
0
10 Sep 2021
Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent
Neural Information Processing Systems (NeurIPS), 2021
Spencer Frei
Quanquan Gu
396
29
0
25 Jun 2021
On Learnability via Gradient Method for Two-Layer ReLU Neural Networks in Teacher-Student Setting
International Conference on Machine Learning (ICML), 2021
Shunta Akiyama
Taiji Suzuki
MLT
337
16
0
11 Jun 2021
Early-stopped neural networks are consistent
Neural Information Processing Systems (NeurIPS), 2021
Ziwei Ji
Justin D. Li
Matus Telgarsky
261
50
0
10 Jun 2021
Learning a Single Neuron with Bias Using Gradient Descent
Neural Information Processing Systems (NeurIPS), 2021
Gal Vardi
Gilad Yehudai
Ohad Shamir
MLT
352
22
0
02 Jun 2021
Directional Convergence Analysis under Spherically Symmetric Distribution
Dachao Lin
Zhihua Zhang
MLT
161
0
0
09 May 2021
Neurons learn slower than they think
I. Kulikovskikh
192
0
0
02 Apr 2021
Painless step size adaptation for SGD
I. Kulikovskikh
Tarzan Legović
207
0
0
01 Feb 2021
Implicit Regularization in ReLU Networks with the Square Loss
Annual Conference Computational Learning Theory (COLT), 2020
Gal Vardi
Ohad Shamir
292
53
0
09 Dec 2020
How Does the Task Landscape Affect MAML Performance?
Liam Collins
Aryan Mokhtari
Sanjay Shakkottai
409
5
0
27 Oct 2020
Understanding How Over-Parametrization Leads to Acceleration: A case of learning a single teacher neuron
Asian Conference on Machine Learning (ACML), 2020
Jun-Kun Wang
Jacob D. Abernethy
347
1
0
04 Oct 2020
A Modular Analysis of Provable Acceleration via Polyak's Momentum: Training a Wide ReLU Network and a Deep Linear Network
International Conference on Machine Learning (ICML), 2020
Jun-Kun Wang
Chi-Heng Lin
Jacob D. Abernethy
726
26
0
04 Oct 2020
Statistical-Query Lower Bounds via Functional Gradients
Surbhi Goel
Aravind Gollakota
Adam R. Klivans
305
68
0
29 Jun 2020
The Effects of Mild Over-parameterization on the Optimization Landscape of Shallow ReLU Neural Networks
Annual Conference Computational Learning Theory (COLT), 2020
Itay Safran
Gilad Yehudai
Ohad Shamir
419
41
0
01 Jun 2020
Agnostic Learning of a Single Neuron with Gradient Descent
Neural Information Processing Systems (NeurIPS), 2020
Spencer Frei
Yuan Cao
Quanquan Gu
MLT
460
66
0
29 May 2020
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