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Gradient Descent Finds Global Minima of Deep Neural Networks

9 November 2018

Papers citing "Gradient Descent Finds Global Minima of Deep Neural Networks"

50 / 466 papers shown

Title
Provable General Function Class Representation Learning in Multitask Bandits and MDPs Rui Lu Andrew Zhao S. Du Gao Huang OffRL 104 10 0 31 May 2022
Non-convex online learning via algorithmic equivalence Udaya Ghai Zhou Lu Elad Hazan 91 11 0 30 May 2022
Do Residual Neural Networks discretize Neural Ordinary Differential Equations? Michael E. Sander Pierre Ablin Gabriel Peyré 112 28 0 29 May 2022
Quadratic models for understanding catapult dynamics of neural networks Libin Zhu Chaoyue Liu Adityanarayanan Radhakrishnan M. Belkin 96 14 0 24 May 2022
Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture Libin Zhu Chaoyue Liu M. Belkin GNN AI4CE 60 4 0 24 May 2022
Gaussian Pre-Activations in Neural Networks: Myth or Reality? Pierre Wolinski Julyan Arbel AI4CE 213 9 0 24 May 2022
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks Blake Bordelon Cengiz Pehlevan MLT 87 85 0 19 May 2022
Policy Gradient Method For Robust Reinforcement Learning Yue Wang Shaofeng Zou 132 77 0 15 May 2022
Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime Hong Hu Yue M. Lu 92 16 0 13 May 2022
Deep Architecture Connectivity Matters for Its Convergence: A Fine-Grained Analysis Wuyang Chen Wei-Ping Huang Xinyu Gong Boris Hanin Zhangyang Wang 89 7 0 11 May 2022
Analysis of convolutional neural network image classifiers in a rotationally symmetric model Michael Kohler Benjamin Kohler 57 5 0 11 May 2022
On Feature Learning in Neural Networks with Global Convergence Guarantees Zhengdao Chen Eric Vanden-Eijnden Joan Bruna MLT 90 13 0 22 Apr 2022
On Convergence Lemma and Convergence Stability for Piecewise Analytic Functions Xiaotie Deng Hanyu Li Ningyuan Li 66 0 0 04 Apr 2022
$Training Fully Connected Neural Networks is $\exists\mathbb{R}$-Complete$ Training Fully Connected Neural Networks is $\exists\mathbb{R}$ -Complete Daniel Bertschinger Christoph Hertrich Paul Jungeblut Tillmann Miltzow Simon Weber OffRL 125 30 0 04 Apr 2022
Convergence of gradient descent for deep neural networks S. Chatterjee ODL 63 22 0 30 Mar 2022
Random matrix analysis of deep neural network weight matrices M. Thamm Max Staats B. Rosenow 74 13 0 28 Mar 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes Elvis Dohmatob A. Bietti AAML 85 13 0 22 Mar 2022
On the Generalization Mystery in Deep Learning S. Chatterjee Piotr Zielinski OOD 75 35 0 18 Mar 2022
On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels Amnon Geifman Meirav Galun David Jacobs Ronen Basri 67 14 0 17 Mar 2022
Towards understanding deep learning with the natural clustering prior Simon Carbonnelle 52 0 0 15 Mar 2022
Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models Chaoyue Liu Libin Zhu M. Belkin 53 4 0 10 Mar 2022
Benefit of Interpolation in Nearest Neighbor Algorithms Yue Xing Qifan Song Guang Cheng 89 30 0 23 Feb 2022
An alternative approach to train neural networks using monotone variational inequality Chen Xu Xiuyuan Cheng Yao Xie 18 1 0 17 Feb 2022
Universality of empirical risk minimization Andrea Montanari Basil Saeed OOD 82 78 0 17 Feb 2022
Benign Overfitting in Two-layer Convolutional Neural Networks Yuan Cao Zixiang Chen M. Belkin Quanquan Gu MLT 93 90 0 14 Feb 2022
Learning from Randomly Initialized Neural Network Features Ehsan Amid Rohan Anil W. Kotłowski Manfred K. Warmuth MLT 79 15 0 13 Feb 2022
Predicting Out-of-Distribution Error with the Projection Norm Yaodong Yu Zitong Yang Alexander Wei Yi-An Ma Jacob Steinhardt OODD 81 44 0 11 Feb 2022
Faster Convergence of Local SGD for Over-Parameterized Models Tiancheng Qin S. Rasoul Etesami César A. Uribe FedML 84 6 0 30 Jan 2022
Understanding Why Generalized Reweighting Does Not Improve Over ERM Runtian Zhai Chen Dan Zico Kolter Pradeep Ravikumar OOD 90 28 0 28 Jan 2022
Convergence of Invariant Graph Networks Chen Cai Yusu Wang 109 4 0 25 Jan 2022
Approximation bounds for norm constrained neural networks with applications to regression and GANs Yuling Jiao Yang Wang Yunfei Yang 78 20 0 24 Jan 2022
Hyperplane bounds for neural feature mappings Antonio Jimeno Yepes 24 2 0 15 Jan 2022
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks Benjamin Bowman Guido Montúfar 106 11 0 12 Jan 2022
AutoBalance: Optimized Loss Functions for Imbalanced Data Mingchen Li Xuechen Zhang Christos Thrampoulidis Jiasi Chen Samet Oymak 71 68 0 04 Jan 2022
Complexity from Adaptive-Symmetries Breaking: Global Minima in the Statistical Mechanics of Deep Neural Networks Shaun Li AI4CE 75 0 0 03 Jan 2022
A Theoretical View of Linear Backpropagation and Its Convergence Ziang Li Yiwen Guo Haodi Liu Changshui Zhang AAML 38 4 0 21 Dec 2021
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 284 350 0 15 Dec 2021
Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time Zhao Song Licheng Zhang Ruizhe Zhang 114 66 0 14 Dec 2021
Convergence proof for stochastic gradient descent in the training of deep neural networks with ReLU activation for constant target functions Martin Hutzenthaler Arnulf Jentzen Katharina Pohl Adrian Riekert Luca Scarpa MLT 112 7 0 13 Dec 2021
Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity Junchi Yang Antonio Orvieto Aurelien Lucchi Niao He 109 64 0 10 Dec 2021
Global convergence of ResNets: From finite to infinite width using linear parameterization Raphael Barboni Gabriel Peyré Franccois-Xavier Vialard 66 12 0 10 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons Fangshuo Liao Anastasios Kyrillidis 118 16 0 05 Dec 2021
Embedding Principle: a hierarchical structure of loss landscape of deep neural networks Yaoyu Zhang Yuqing Li Zhongwang Zhang Yaoyu Zhang Z. Xu 84 23 0 30 Nov 2021
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization Thanh Nguyen-Tang Sunil R. Gupta A. Nguyen Svetha Venkatesh OffRL 97 30 0 27 Nov 2021
KNAS: Green Neural Architecture Search Jingjing Xu Liang Zhao Junyang Lin Rundong Gao Xu Sun Hongxia Yang 76 59 0 26 Nov 2021
On the Equivalence between Neural Network and Support Vector Machine Yilan Chen Wei Huang Lam M. Nguyen Tsui-Wei Weng AAML 73 18 0 11 Nov 2021
SGD Through the Lens of Kolmogorov Complexity Gregory Schwartzman 75 1 0 10 Nov 2021
Mode connectivity in the loss landscape of parameterized quantum circuits Kathleen E. Hamilton E. Lynn R. Pooser 56 3 0 09 Nov 2021
Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs Guang Lin Christian Moya Zecheng Zhang 76 30 0 03 Nov 2021
Dynamics of Local Elasticity During Training of Neural Nets Soham Dan Anirbit Mukherjee Avirup Das Phanideep Gampa 52 0 0 01 Nov 2021