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1803.01206
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On the Power of Over-parametrization in Neural Networks with Quadratic Activation
3 March 2018
S. Du
J. Lee
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Papers citing
"On the Power of Over-parametrization in Neural Networks with Quadratic Activation"
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Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion
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Analysis of the rate of convergence of an over-parametrized convolutional neural network image classifier learned by gradient descent
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Variational Stochastic Gradient Descent for Deep Neural Networks
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Anna Kuzina
Babak Esmaeili
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Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding
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The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks
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Critical Influence of Overparameterization on Sharpness-aware Minimization
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Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable Regression
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Global Convergence of SGD On Two Layer Neural Nets
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Interpretable Polynomial Neural Ordinary Differential Equations
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Neural Networks can Learn Representations with Gradient Descent
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Mahdi Soltanolkotabi
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Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials
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Yunzhi Bai
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Embedding Principle in Depth for the Loss Landscape Analysis of Deep Neural Networks
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Tao Luo
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Knowledge Distillation Meets Open-Set Semi-Supervised Learning
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Adrian Bulat
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The Spectral Bias of Polynomial Neural Networks
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Benefit of Interpolation in Nearest Neighbor Algorithms
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Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably
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Enlu Zhou
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34
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Over-Parametrized Matrix Factorization in the Presence of Spurious Stationary Points
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Subquadratic Overparameterization for Shallow Neural Networks
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Path Regularization: A Convexity and Sparsity Inducing Regularization for Parallel ReLU Networks
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Mert Pilanci
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On the Global Convergence of Gradient Descent for multi-layer ResNets in the mean-field regime
Zhiyan Ding
Shi Chen
Qin Li
S. Wright
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Exponentially Many Local Minima in Quantum Neural Networks
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Xiaodi Wu
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Tensor Methods in Computer Vision and Deep Learning
Yannis Panagakis
Jean Kossaifi
Grigorios G. Chrysos
James Oldfield
M. Nicolaou
Anima Anandkumar
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07 Jul 2021
Landscape analysis for shallow neural networks: complete classification of critical points for affine target functions
Patrick Cheridito
Arnulf Jentzen
Florian Rossmannek
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A Convergence Theory Towards Practical Over-parameterized Deep Neural Networks
Asaf Noy
Yi Tian Xu
Y. Aflalo
Lihi Zelnik-Manor
R. L. Jin
33
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12 Jan 2021
Learning Graph Neural Networks with Approximate Gradient Descent
Qunwei Li
Shaofeng Zou
Leon Wenliang Zhong
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A Dynamical View on Optimization Algorithms of Overparameterized Neural Networks
Zhiqi Bu
Shiyun Xu
Kan Chen
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17
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Understanding Self-supervised Learning with Dual Deep Networks
Yuandong Tian
Lantao Yu
Xinlei Chen
Surya Ganguli
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Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't
E. Weinan
Chao Ma
Stephan Wojtowytsch
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133
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Recurrent Quantum Neural Networks
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151
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25 Jun 2020
Learning the gravitational force law and other analytic functions
Atish Agarwala
Abhimanyu Das
Rina Panigrahy
Qiuyi Zhang
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15 May 2020
Convex Geometry and Duality of Over-parameterized Neural Networks
Tolga Ergen
Mert Pilanci
MLT
36
54
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25 Feb 2020
Revisiting Landscape Analysis in Deep Neural Networks: Eliminating Decreasing Paths to Infinity
Shiyu Liang
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35
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Optimization for deep learning: theory and algorithms
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168
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The Local Elasticity of Neural Networks
Hangfeng He
Weijie J. Su
40
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Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks
Yu Bai
J. Lee
24
116
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Neural ODEs as the Deep Limit of ResNets with constant weights
B. Avelin
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37
31
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28 Jun 2019
Gradient Descent Maximizes the Margin of Homogeneous Neural Networks
Kaifeng Lyu
Jian Li
43
321
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13 Jun 2019
Global Optimality Guarantees For Policy Gradient Methods
Jalaj Bhandari
Daniel Russo
35
185
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Fine-grained Optimization of Deep Neural Networks
Mete Ozay
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14
1
0
22 May 2019
Every Local Minimum Value is the Global Minimum Value of Induced Model in Non-convex Machine Learning
Kenji Kawaguchi
Jiaoyang Huang
L. Kaelbling
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18
18
0
07 Apr 2019
T-Net: Parametrizing Fully Convolutional Nets with a Single High-Order Tensor
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Adrian Bulat
Georgios Tzimiropoulos
M. Pantic
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67
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Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks
Sanjeev Arora
S. Du
Wei Hu
Zhiyuan Li
Ruosong Wang
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35
962
0
24 Jan 2019
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