Effect of Activation Functions on the Training of Overparametrized Neural Nets | Paper Citation Record

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This paper cites Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers

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This paper cites A convergence theory for deep learning via over-parameterization.

Effect of Activation Functions on the Training of Overparametrized Neural Nets A convergence theory for deep learning via over-parameterization

Reference 2

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Effect of Activation Functions on the Training of Overparametrized Neural Nets Unresolved cited work

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This paper cites A convergence analysis of gradient descent for deep linear neural networks.

Effect of Activation Functions on the Training of Overparametrized Neural Nets A convergence analysis of gradient descent for deep linear neural networks

Reference 4

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This paper cites On exact computation with an infinitely wide neural net.

Effect of Activation Functions on the Training of Overparametrized Neural Nets On exact computation with an infinitely wide neural net

Reference 5

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This paper cites Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks

Reference 6

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This paper cites Concentration inequalities.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Concentration inequalities

Reference 7

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This paper cites Asymptotic coefficients of hermite function series.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Asymptotic coefficients of hermite function series

Reference 8

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This paper cites SGD learns over-parameterized networks that provably generalize on linearly separable data.

Effect of Activation Functions on the Training of Overparametrized Neural Nets SGD learns over-parameterized networks that provably generalize on linearly separable data

Reference 9

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This paper cites Distributional and L^q norm inequalities for polynomials over convex bodies in R^n.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Distributional and L^q norm inequalities for polynomials over convex bodies in R^n

Reference 10

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This paper cites On the global convergence of gradient descent for over-parameterized models using optimal transport.

Effect of Activation Functions on the Training of Overparametrized Neural Nets On the global convergence of gradient descent for over-parameterized models using optimal transport

Reference 11

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This paper cites Fast and accurate deep network learning by exponential linear units (elus).

Effect of Activation Functions on the Training of Overparametrized Neural Nets Fast and accurate deep network learning by exponential linear units (elus)

Reference 12

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This paper cites Toward deeper understanding of neural networks: The power of initialization and a dual view on expressivity.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Toward deeper understanding of neural networks: The power of initialization and a dual view on expressivity

Reference 13

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This paper cites Du and Jason D.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Du and Jason D

Reference 14

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This paper cites Du, Xiyu Zhai, Barnabas Poczos, and Aarti Singh.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Du, Xiyu Zhai, Barnabas Poczos, and Aarti Singh

Reference 15

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This paper cites Lee, Haochuan Li, Liwei Wang, and Xiyu Zhai.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Lee, Haochuan Li, Liwei Wang, and Xiyu Zhai

Reference 16

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This paper cites Is it time to swish? comparing deep learning activation functions across nlp tasks.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Is it time to swish? comparing deep learning activation functions across nlp tasks

Reference 17

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This paper cites Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning

Reference 18

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This paper cites Understanding the difficulty of training deep feedforward neural networks.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Understanding the difficulty of training deep feedforward neural networks

Reference 19

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This paper cites Deep Learning.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Deep Learning

Reference 20

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This paper cites Which neural net architectures give rise to exploding and vanishing gradients? In S.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Which neural net architectures give rise to exploding and vanishing gradients? In S

Reference 21

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This paper cites How to start training: The effect of initialization and architecture.

Effect of Activation Functions on the Training of Overparametrized Neural Nets How to start training: The effect of initialization and architecture

Reference 22

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This paper cites On the Impact of the Activation Function on Deep Neural Networks Training.

Effect of Activation Functions on the Training of Overparametrized Neural Nets On the Impact of the Activation Function on Deep Neural Networks Training

Reference 23

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This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Delving deep into rectifiers: Surpassing human-level performance on imagenet classification

Reference 24

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This paper cites Contributions to the theory of H ermitian series.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Contributions to the theory of H ermitian series

Reference 25

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This paper cites Neural tangent kernel: Convergence and generalization in neural networks.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Neural tangent kernel: Convergence and generalization in neural networks

Reference 26

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This paper cites Solutions to some functional equations and their applications to characterization of probability distributions.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Solutions to some functional equations and their applications to characterization of probability distributions

Reference 27

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This paper cites On the expressive power of deep polynomial neural networks.

Effect of Activation Functions on the Training of Overparametrized Neural Nets On the expressive power of deep polynomial neural networks

Reference 28

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Effect of Activation Functions on the Training of Overparametrized Neural Nets Self-normalizing neural networks

Reference 29

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This paper cites Learning multiple layers of features from tiny images.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Learning multiple layers of features from tiny images

Reference 30

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This paper cites Adaptive estimation of a quadratic functional by model selection.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Adaptive estimation of a quadratic functional by model selection

Reference 31

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Effect of Activation Functions on the Training of Overparametrized Neural Nets Unresolved cited work

Reference 32

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This paper cites Deep Neural Networks as Gaussian Processes.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Deep Neural Networks as Gaussian Processes

Reference 33

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This paper cites Lin, Allan Pinkus, and Shimon Schocken.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Lin, Allan Pinkus, and Shimon Schocken

Reference 34

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This paper cites Learning overparameterized neural networks via stochastic gradient descent on structured data.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Learning overparameterized neural networks via stochastic gradient descent on structured data

Reference 35

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This paper cites A random matrix approach to neural networks.

Effect of Activation Functions on the Training of Overparametrized Neural Nets A random matrix approach to neural networks

Reference 36

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This paper cites Mason and D.C.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Mason and D.C

Reference 37

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This paper cites A mean field view of the landscape of two-layer neural networks.

Effect of Activation Functions on the Training of Overparametrized Neural Nets A mean field view of the landscape of two-layer neural networks

Reference 38

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This paper cites In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning.

Effect of Activation Functions on the Training of Overparametrized Neural Nets In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning

Reference 39

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This paper cites Activation Functions: Comparison of trends in Practice and Research for Deep Learning.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Activation Functions: Comparison of trends in Practice and Research for Deep Learning

Reference 40

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This paper cites Analysis of boolean functions.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Analysis of boolean functions

Reference 41

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This paper cites Towards moderate overparameterization: global convergence guarantees for training shallow neural networks.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Towards moderate overparameterization: global convergence guarantees for training shallow neural networks

Reference 42

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This paper cites Nonlinear random matrix theory for deep learning.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Nonlinear random matrix theory for deep learning

Reference 43

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This paper cites The spectrum of the fisher information matrix of a single-hidden-layer neural network.

Effect of Activation Functions on the Training of Overparametrized Neural Nets The spectrum of the fisher information matrix of a single-hidden-layer neural network

Reference 44

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This paper cites Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:02:30.285600Z

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Observation 9419fa2b-9418-4b64-96b4-24e0d17f8e89 · outbound

This paper cites Schoenholz, and Surya Ganguli.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Schoenholz, and Surya Ganguli

Reference 46

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This paper cites Approximation theory of the MLP model in neural networks.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Approximation theory of the MLP model in neural networks

Reference 47

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Effect of Activation Functions on the Training of Overparametrized Neural Nets Unresolved cited work

Reference 48

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This paper cites Smallest singular value of a random rectangular matrix.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Smallest singular value of a random rectangular matrix

Reference 49

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Observation 1f5371f0-0ba6-4aeb-ae0a-3ac7a7fe71d0 · outbound

This paper cites Learning kernel-based halfspaces with the 0-1 loss.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Learning kernel-based halfspaces with the 0-1 loss

Reference 50

Resolution: verified exact; doi, observed 2026-08-14T13:02:29.866153Z

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This paper cites Neural network with unbounded activation functions is universal approximator.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Neural network with unbounded activation functions is universal approximator

Reference 51

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This paper cites Spielman and Shang - Hua Teng.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Spielman and Shang - Hua Teng

Reference 52

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This paper cites Orthogonal polynomials.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Orthogonal polynomials

Reference 53

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This paper cites Lectures on H ermite and L aguerre expansions , volume 42 of Mathematical Notes.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Lectures on H ermite and L aguerre expansions , volume 42 of Mathematical Notes

Reference 54

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This paper cites Invariance of weight distributions in rectified mlps.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Invariance of weight distributions in rectified mlps

Reference 55

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Observation 1ad9c1a3-2098-49b3-9278-8d33845db6d9 · outbound

This paper cites Ger s gorin and his circles , volume 36.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Ger s gorin and his circles , volume 36

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:02:30.197116Z

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Observation 75988217-aebb-44a7-9e99-78be683f461c · outbound

This paper cites Das asymptotische V erteilungsgesetz der E igenwerte linearer partieller D ifferentialgleichungen (mit einer A nwendung auf die T heorie der H ohlraumstrahlung).

Effect of Activation Functions on the Training of Overparametrized Neural Nets Das asymptotische V erteilungsgesetz der E igenwerte linearer partieller D ifferentialgleichungen (mit einer A nwendung auf die T heorie der H ohlraumstrahlung)

Reference 57

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Observation 461b217f-a1a3-4c04-87cc-c61dd1fc5b81 · outbound

This paper cites Diverse neural network learns true target functions.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Diverse neural network learns true target functions

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:02:30.183720Z

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Observation 9211ccd6-05ec-414f-9838-f3c65a5f081c · outbound

This paper cites Revise saturated activation functions.

Effect of Activation Functions on the Training of Overparametrized Neural Nets Revise saturated activation functions

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T13:02:30.170883Z

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