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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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From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality Fusheng Liu Haizhao Yang Soufiane Hayou Qianxiao Li AI4CE 81 2 0 22 Feb 2022
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Random Feature Amplification: Feature Learning and Generalization in Neural Networks Spencer Frei Niladri S. Chatterji Peter L. Bartlett MLT 103 30 0 15 Feb 2022
Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution Generalization Elan Rosenfeld Pradeep Ravikumar Andrej Risteski OOD 88 82 0 14 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
Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data Spencer Frei Niladri S. Chatterji Peter L. Bartlett MLT 110 75 0 11 Feb 2022
Deep Learning in Random Neural Fields: Numerical Experiments via Neural Tangent Kernel Kaito Watanabe Kotaro Sakamoto Ryo Karakida Sho Sonoda S. Amari OOD 130 1 0 10 Feb 2022
Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets Tianlong Chen Xuxi Chen Xiaolong Ma Yanzhi Wang Zhangyang Wang 82 34 0 09 Feb 2022
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably Tianyi Liu Yan Li Enlu Zhou Tuo Zhao 62 1 0 07 Feb 2022
Finite-Sum Optimization: A New Perspective for Convergence to a Global Solution Lam M. Nguyen Trang H. Tran Marten van Dijk 102 3 0 07 Feb 2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning Wei Huang Chunrui Liu Yilan Chen Tianyu Liu R. Xu BDL MLT 67 2 0 04 Feb 2022
Improved Overparametrization Bounds for Global Convergence of Stochastic Gradient Descent for Shallow Neural Networks Bartlomiej Polaczyk J. Cyranka ODL 61 3 0 28 Jan 2022
Convergence of Invariant Graph Networks Chen Cai Yusu Wang 109 4 0 25 Jan 2022
STOPS: Short-Term-based Volatility-controlled Policy Search and its Global Convergence Liang Xu Daoming Lyu Yangchen Pan Aiwen Jiang Bo Liu 95 0 0 24 Jan 2022
How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis Shuai Zhang Ming Wang Sijia Liu Pin-Yu Chen Jinjun Xiong SSL MLT 111 23 0 21 Jan 2022
Accelerated Gradient Flow: Risk, Stability, and Implicit Regularization Yue Sheng Alnur Ali 122 2 0 20 Jan 2022
Learning Neural Ranking Models Online from Implicit User Feedback Yiling Jia Hongning Wang 94 6 0 17 Jan 2022
Towards Sample-efficient Overparameterized Meta-learning Yue Sun Adhyyan Narang Halil Ibrahim Gulluk Samet Oymak Maryam Fazel BDL 68 25 0 16 Jan 2022
Largest Eigenvalues of the Conjugate Kernel of Single-Layered Neural Networks L. Benigni Sandrine Péché 83 8 0 13 Jan 2022
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks Benjamin Bowman Guido Montúfar 106 11 0 12 Jan 2022
Neural calibration of hidden inhomogeneous Markov chains -- Information decompression in life insurance Mark Kiermayer Christian Weiß 38 0 0 07 Jan 2022
Efficient Global Optimization of Two-Layer ReLU Networks: Quadratic-Time Algorithms and Adversarial Training Yatong Bai Tanmay Gautam Somayeh Sojoudi AAML 112 17 0 06 Jan 2022
Stochastic Continuous Submodular Maximization: Boosting via Non-oblivious Function Qixin Zhang Zengde Deng Zaiyi Chen Haoyuan Hu Yu Yang 84 20 0 03 Jan 2022
A Theoretical View of Linear Backpropagation and Its Convergence Ziang Li Yiwen Guo Haodi Liu Changshui Zhang AAML 41 4 0 21 Dec 2021
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime Rui Zhang Shihua Zhang TDI 70 23 0 15 Dec 2021
Decomposing the Deep: Finding Class Specific Filters in Deep CNNs Akshay Badola Cherian Roy V. Padmanabhan R. Lal FAtt 64 2 0 14 Dec 2021
Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time Zhao Song Licheng Zhang Ruizhe Zhang 116 66 0 14 Dec 2021
SCORE: Approximating Curvature Information under Self-Concordant Regularization Adeyemi Damilare Adeoye Alberto Bemporad 44 4 0 14 Dec 2021
Eigenspace Restructuring: a Principle of Space and Frequency in Neural Networks Lechao Xiao 110 22 0 10 Dec 2021
Global convergence of ResNets: From finite to infinite width using linear parameterization Raphael Barboni Gabriel Peyré Franccois-Xavier Vialard 68 12 0 10 Dec 2021
Provable Continual Learning via Sketched Jacobian Approximations Reinhard Heckel CLL 78 10 0 09 Dec 2021
Understanding Square Loss in Training Overparametrized Neural Network Classifiers Tianyang Hu Jun Wang Wei Cao Zhenguo Li UQCV AAML 92 19 0 07 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons Fangshuo Liao Anastasios Kyrillidis 120 16 0 05 Dec 2021
Fast Graph Neural Tangent Kernel via Kronecker Sketching Shunhua Jiang Yunze Man Zhao Song Zheng Yu Danyang Zhuo 96 6 0 04 Dec 2021
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models Tri Dao Beidi Chen Kaizhao Liang Jiaming Yang Zhao Song Atri Rudra Christopher Ré 133 79 0 30 Nov 2021
Generalization Performance of Empirical Risk Minimization on Over-parameterized Deep ReLU Nets Shao-Bo Lin Yao Wang Ding-Xuan Zhou ODL 92 6 0 28 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 78 59 0 26 Nov 2021
Modeling Design and Control Problems Involving Neural Network Surrogates Dominic Yang Prasanna Balaprakash S. Leyffer 55 15 0 20 Nov 2021
Benchmarking and scaling of deep learning models for land cover image classification Ioannis Papoutsis Nikolaos Ioannis Bountos Angelos Zavras Dimitrios Michail Christos Tryfonopoulos 108 61 0 18 Nov 2021
Learning with convolution and pooling operations in kernel methods Theodor Misiakiewicz Song Mei MLT 90 29 0 16 Nov 2021
The Three Stages of Learning Dynamics in High-Dimensional Kernel Methods Nikhil Ghosh Song Mei Bin Yu 73 20 0 13 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
Theoretical Exploration of Flexible Transmitter Model Jin-Hui Wu Shao-Qun Zhang Yuan Jiang Zhiping Zhou 63 3 0 11 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
Subquadratic Overparameterization for Shallow Neural Networks Chaehwan Song Ali Ramezani-Kebrya Thomas Pethick Armin Eftekhari Volkan Cevher 81 31 0 02 Nov 2021
Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias Kaifeng Lyu Zhiyuan Li Runzhe Wang Sanjeev Arora MLT 110 76 0 26 Oct 2021
Quantifying Epistemic Uncertainty in Deep Learning Ziyi Huang Henry Lam Haofeng Zhang UQCV BDL UD PER 134 14 0 23 Oct 2021
UniFed: A Unified Framework for Federated Learning on Non-IID Image Features Meirui Jiang Xiaoxiao Li Xiaofei Zhang Michael Kamp Qianming Dou FedML OOD 100 0 0 19 Oct 2021
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game Shuang Qiu Jieping Ye Zhaoran Wang Zhuoran Yang OffRL 104 23 0 19 Oct 2021