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Gradient Descent Provably Optimizes Over-parameterized Neural Networks

4 October 2018

Aarti Singh

Papers citing "Gradient Descent Provably Optimizes Over-parameterized Neural Networks"

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Title
Addressing the Inconsistency in Bayesian Deep Learning via Generalized Laplace Approximation Yinsong Chen Samson S. Yu Zhong Li Chee Peng Lim BDL 80 0 0 01 Jul 2025
Generalization Bound of Gradient Flow through Training Trajectory and Data-dependent Kernel Yilan Chen Zhichao Wang Wei Huang Andi Han Taiji Suzuki Arya Mazumdar MLT 24 0 0 12 Jun 2025
Sharper Convergence Rates for Nonconvex Optimisation via Reduction Mappings Evan Markou Thalaiyasingam Ajanthan Stephen Gould 31 0 0 10 Jun 2025
Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation Zhan Zhuang Xiequn Wang Wei Li Yulong Zhang Qiushi Huang ... Yanbin Wei Yuhe Nie Kede Ma Yu Zhang Ying Wei 57 0 0 06 Jun 2025
Implicit Regularization of the Deep Inverse Prior Trained with Inertia Nathan Buskulic Jalal Fadil Yvain Quéau 47 1 0 03 Jun 2025
SGD as Free Energy Minimization: A Thermodynamic View on Neural Network Training Ildus Sadrtdinov Ivan Klimov E. Lobacheva Dmitry Vetrov 32 0 0 29 May 2025
Benignity of loss landscape with weight decay requires both large overparametrization and initialization Etienne Boursier Matthew Bowditch Matthias Englert R. Lazic 42 0 0 28 May 2025
Assessing Quantum Advantage for Gaussian Process Regression Dominic Lowe M.S. Kim Roberto Bondesan 36 1 0 28 May 2025
Saddle-To-Saddle Dynamics in Deep ReLU Networks: Low-Rank Bias in the First Saddle Escape Ioannis Bantzis James B. Simon Arthur Jacot ODL 54 0 0 27 May 2025
Convexified Message-Passing Graph Neural Networks Saar Cohen Noa Agmon Uri Shaham GNN 41 0 0 23 May 2025
Convergence of Adam in Deep ReLU Networks via Directional Complexity and Kakeya Bounds Anupama Sridhar Alexander Johansen 80 0 0 21 May 2025
New Evidence of the Two-Phase Learning Dynamics of Neural Networks Zhanpeng Zhou Yongyi Yang Mahito Sugiyama Junchi Yan 35 0 0 20 May 2025
A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models Ziqing Xu Hancheng Min Salma Tarmoun Enrique Mallada Rene Vidal 125 0 0 16 May 2025
The Power of Random Features and the Limits of Distribution-Free Gradient Descent Ari Karchmer Eran Malach 89 0 0 15 May 2025
Neural Multivariate Regression: Qualitative Insights from the Unconstrained Feature Model Shuyang Ling Soyuj Jung Basnet Juan Guevara Li Guo George Andriopoulos 81 0 0 14 May 2025
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime Francesco Camilli D. Tieplova Eleonora Bergamin Jean Barbier 418 2 0 06 May 2025
Deep Learning Optimization Using Self-Adaptive Weighted Auxiliary Variables Yaru Liu Yiqi Gu Michael K. Ng ODL 89 0 0 30 Apr 2025
Deep learning with missing data Tianyi Ma Tengyao Wang R. Samworth 271 1 0 21 Apr 2025
Divergence of Empirical Neural Tangent Kernel in Classification Problems Zixiong Yu Songtao Tian Guhan Chen 70 0 0 15 Apr 2025
Towards Understanding the Optimization Mechanisms in Deep Learning Binchuan Qi Wei Gong Li Li 95 0 0 29 Mar 2025
Feature Learning beyond the Lazy-Rich Dichotomy: Insights from Representational Geometry Chi-Ning Chou Hang Le Yichen Wang SueYeon Chung 92 0 0 23 Mar 2025
NeuroSep-CP-LCB: A Deep Learning-based Contextual Multi-armed Bandit Algorithm with Uncertainty Quantification for Early Sepsis Prediction Anni Zhou Raheem Beyah Rishikesan Kamaleswaran 103 0 0 20 Mar 2025
On the Cone Effect in the Learning Dynamics Zhanpeng Zhou Yongyi Yang Jie Ren Mahito Sugiyama Junchi Yan 116 0 0 20 Mar 2025
Neural Tangent Kernel of Neural Networks with Loss Informed by Differential Operators Weiye Gan Yicheng Li Q. Lin Zuoqiang Shi 75 0 0 14 Mar 2025
Global Convergence and Rich Feature Learning in $L$ -Layer Infinite-Width Neural Networks under $μ$ P Parametrization Zixiang Chen Greg Yang Qingyue Zhao Q. Gu MLT 86 0 0 12 Mar 2025
A Near Complete Nonasymptotic Generalization Theory For Multilayer Neural Networks: Beyond the Bias-Variance Tradeoff Hao Yu Xiangyang Ji AI4CE 79 0 0 03 Mar 2025
Scaling Law Phenomena Across Regression Paradigms: Multiple and Kernel Approaches Yifang Chen Xuyang Guo Xiaoyu Li Yingyu Liang Zhenmei Shi Zhao Song 103 3 0 03 Mar 2025
On the Saturation Effects of Spectral Algorithms in Large Dimensions Weihao Lu Haobo Zhang Yicheng Li Q. Lin 109 2 0 01 Mar 2025
Low-rank bias, weight decay, and model merging in neural networks Ilja Kuzborskij Yasin Abbasi-Yadkori 81 0 0 24 Feb 2025
Convergence of Shallow ReLU Networks on Weakly Interacting Data Léo Dana Francis R. Bach Loucas Pillaud-Vivien MLT 95 2 0 24 Feb 2025
Mesterséges Intelligencia Kutatások Magyarországon András A. Benczúr Tibor Gyimóthy Balázs Szegedy VLM 103 0 0 24 Feb 2025
Explainable Neural Networks with Guarantees: A Sparse Estimation Approach Antoine Ledent Peng Liu FAtt 355 0 0 20 Feb 2025
Curse of Dimensionality in Neural Network Optimization Sanghoon Na Haizhao Yang 89 0 0 07 Feb 2025
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input Ziang Chen Rong Ge MLT 152 1 0 10 Jan 2025
A Riemannian Optimization Perspective of the Gauss-Newton Method for Feedforward Neural Networks Semih Cayci 139 0 0 18 Dec 2024
Gradient Descent Finds Over-Parameterized Neural Networks with Sharp Generalization for Nonparametric Regression Yingzhen Yang Ping Li MLT 107 0 0 05 Nov 2024
Generalizability of Memorization Neural Networks Lijia Yu Xiao-Shan Gao Lijun Zhang Yibo Miao 99 1 0 01 Nov 2024
CopRA: A Progressive LoRA Training Strategy Zhan Zhuang Xiequn Wang Yulong Zhang Wei Li Yu Zhang Ying Wei 114 1 0 30 Oct 2024
Inductive Gradient Adjustment For Spectral Bias In Implicit Neural Representations Kexuan Shi Hai Chen Leheng Zhang Shuhang Gu 95 1 0 17 Oct 2024
Towards Sharper Risk Bounds for Minimax Problems Bowei Zhu Shaojie Li Yong Liu 76 0 0 11 Oct 2024
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data Binghui Li Yuanzhi Li OOD 94 4 0 11 Oct 2024
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory Guhan Chen Yicheng Li Qian Lin AAML 73 1 0 08 Oct 2024
Extended convexity and smoothness and their applications in deep learning Binchuan Qi Wei Gong Li Li 117 0 0 08 Oct 2024
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks Clémentine Dominé Nicolas Anguita A. Proca Lukas Braun D. Kunin P. Mediano Andrew M. Saxe 138 6 0 22 Sep 2024
On the Convergence Analysis of Over-Parameterized Variational Autoencoders: A Neural Tangent Kernel Perspective Li Wang Wei Huang DRL 99 0 0 09 Sep 2024
Beyond Unconstrained Features: Neural Collapse for Shallow Neural Networks with General Data Wanli Hong Shuyang Ling 71 4 0 03 Sep 2024
Improving Adaptivity via Over-Parameterization in Sequence Models Yicheng Li Qian Lin 84 1 0 02 Sep 2024
On the Pinsker bound of inner product kernel regression in large dimensions Weihao Lu Jialin Ding Haobo Zhang Qian Lin 93 1 0 02 Sep 2024
Absence of Closed-Form Descriptions for Gradient Flow in Two-Layer Narrow Networks Yeachan Park AI4CE 119 0 0 15 Aug 2024
Hybrid Coordinate Descent for Efficient Neural Network Learning Using Line Search and Gradient Descent Yen-Che Hsiao Abhishek Dutta 106 0 0 02 Aug 2024