Learning a Single Neuron with Gradient Methods

15 January 2020

Papers citing "Learning a Single Neuron with Gradient Methods"

14 / 14 papers shown

Title
Low-dimensional Functions are Efficiently Learnable under Randomly Biased Distributions Elisabetta Cornacchia Dan Mikulincer Elchanan Mossel 79 1 0 10 Feb 2025
Bayesian Inference for Consistent Predictions in Overparameterized Nonlinear Regression Tomoya Wakayama BDL 57 0 0 06 Apr 2024
Symmetric Single Index Learning Aaron Zweig Joan Bruna MLT 36 2 0 03 Oct 2023
Gradient-Based Feature Learning under Structured Data Alireza Mousavi-Hosseini Denny Wu Taiji Suzuki Murat A. Erdogdu MLT 39 18 0 07 Sep 2023
On Single Index Models beyond Gaussian Data Joan Bruna Loucas Pillaud-Vivien Aaron Zweig 20 10 0 28 Jul 2023
Over-Parameterization Exponentially Slows Down Gradient Descent for Learning a Single Neuron Weihang Xu S. Du 39 16 0 20 Feb 2023
Active Learning for Single Neuron Models with Lipschitz Non-Linearities Aarshvi Gajjar C. Hegde Christopher Musco 32 12 0 24 Oct 2022
SQ Lower Bounds for Learning Single Neurons with Massart Noise Ilias Diakonikolas D. Kane Lisheng Ren Yuxin Sun 25 6 0 18 Oct 2022
Magnitude and Angle Dynamics in Training Single ReLU Neurons Sangmin Lee Byeongsu Sim Jong Chul Ye MLT 96 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 41 124 0 18 Jul 2022
Random Feature Amplification: Feature Learning and Generalization in Neural Networks Spencer Frei Niladri S. Chatterji Peter L. Bartlett MLT 30 29 0 15 Feb 2022
Optimization-Based Separations for Neural Networks Itay Safran Jason D. Lee 203 14 0 04 Dec 2021
ReLU Regression with Massart Noise Ilias Diakonikolas Jongho Park Christos Tzamos 56 11 0 10 Sep 2021
Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent Spencer Frei Quanquan Gu 26 26 0 25 Jun 2021