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Agnostic Learning of a Single Neuron with Gradient Descent

29 May 2020

Quanquan Gu

Papers citing "Agnostic Learning of a Single Neuron with Gradient Descent"

25 / 25 papers shown

Title
Low-dimensional Functions are Efficiently Learnable under Randomly Biased Distributions Elisabetta Cornacchia Dan Mikulincer Elchanan Mossel 180 1 0 10 Feb 2025
Disentangle Sample Size and Initialization Effect on Perfect Generalization for Single-Neuron Target Jiajie Zhao Zhiwei Bai Yaoyu Zhang 97 0 0 22 May 2024
Masks, Signs, And Learning Rate Rewinding Advait Gadhikar R. Burkholz 144 12 0 29 Feb 2024
Differentially Private Non-convex Learning for Multi-layer Neural Networks Hanpu Shen Cheng-Long Wang Zihang Xiang Yiming Ying Di Wang 137 8 0 12 Oct 2023
How Graph Neural Networks Learn: Lessons from Training Dynamics Chenxiao Yang Qitian Wu David Wipf Ruoyu Sun Junchi Yan AI4CE GNN 170 2 0 08 Oct 2023
Robustly Learning a Single Neuron via Sharpness Puqian Wang Nikos Zarifis Ilias Diakonikolas Jelena Diakonikolas 108 11 0 13 Jun 2023
Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron Jingfeng Wu Difan Zou Zixiang Chen Vladimir Braverman Quanquan Gu Sham Kakade 179 8 0 03 Mar 2023
Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals Ilias Diakonikolas D. Kane Lisheng Ren 106 31 0 13 Feb 2023
Magnitude and Angle Dynamics in Training Single ReLU Neurons Sangmin Lee Byeongsu Sim Jong Chul Ye MLT 199 6 0 27 Sep 2022
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit Boaz Barak Benjamin L. Edelman Surbhi Goel Sham Kakade Eran Malach Cyril Zhang 188 141 0 18 Jul 2022
Learning a Single Neuron with Adversarial Label Noise via Gradient Descent Ilias Diakonikolas Vasilis Kontonis Christos Tzamos Nikos Zarifis MLT 69 22 0 17 Jun 2022
Learning a Single Neuron for Non-monotonic Activation Functions Lei Wu MLT 85 12 0 16 Feb 2022
Random Feature Amplification: Feature Learning and Generalization in Neural Networks Spencer Frei Niladri S. Chatterji Peter L. Bartlett MLT 178 31 0 15 Feb 2022
Optimization-Based Separations for Neural Networks Itay Safran Jason D. Lee 503 14 0 04 Dec 2021
Dynamics of Local Elasticity During Training of Neural Nets Soham Dan Anirbit Mukherjee Avirup Das Phanideep Gampa 156 0 0 01 Nov 2021
ReLU Regression with Massart Noise Ilias Diakonikolas Jongho Park Christos Tzamos 135 12 0 10 Sep 2021
Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent Spencer Frei Quanquan Gu 154 28 0 25 Jun 2021
On the Cryptographic Hardness of Learning Single Periodic Neurons M. Song Ilias Zadik Joan Bruna AAML 93 31 0 20 Jun 2021
Early-stopped neural networks are consistent Ziwei Ji Justin D. Li Matus Telgarsky 158 43 0 10 Jun 2021
Learning a Single Neuron with Bias Using Gradient Descent Gal Vardi Gilad Yehudai Ohad Shamir MLT 142 18 0 02 Jun 2021
Painless step size adaptation for SGD I. Kulikovskikh Tarzan Legović 97 0 0 01 Feb 2021
The Connection Between Approximation, Depth Separation and Learnability in Neural NetworksAnnual Conference Computational Learning Theory (COLT), 2024 Eran Malach Gilad Yehudai Shai Shalev-Shwartz Ohad Shamir 135 20 0 31 Jan 2021
Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise Spencer Frei Yuan Cao Quanquan Gu FedML MLT 264 22 0 04 Jan 2021
Statistical-Query Lower Bounds via Functional Gradients Surbhi Goel Aravind Gollakota Adam R. Klivans 121 64 0 29 Jun 2020
The role of optimization geometry in single neuron learningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025 Nicholas M. Boffi Stephen Tu Jean-Jacques E. Slotine 84 1 0 15 Jun 2020