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Estimation error analysis of deep learning on the regression problem on the variable exponent Besov space
23 September 2020
Kazuma Tsuji
Taiji Suzuki
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ArXiv (abs)
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Papers citing
"Estimation error analysis of deep learning on the regression problem on the variable exponent Besov space"
14 / 14 papers shown
Title
Deep learning from strongly mixing observations: Sparse-penalized regularization and minimax optimality
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Robust deep learning from weakly dependent data
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Sup-Norm Convergence of Deep Neural Network Estimator for Nonparametric Regression by Adversarial Training
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Penalized deep neural networks estimator with general loss functions under weak dependence
William Kengne
Modou Wade
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10 May 2023
Pointwise convergence of Fourier series and deep neural network for the indicator function of d-dimensional ball
Ryota Kawasumi
Tsuyoshi Yoneda
18
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17 Apr 2023
Pairwise Ranking with Gaussian Kernels
Guanhang Lei
Lei Shi
89
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06 Apr 2023
Sparse-penalized deep neural networks estimator under weak dependence
William Kengne
Modou Wade
64
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02 Mar 2023
Confidence-Nets: A Step Towards better Prediction Intervals for regression Neural Networks on small datasets
M. Altayeb
A. Elamin
Hozaifa Ahmed
Eithar Elfatih Elfadil Ibrahim
Omer Haydar
Saba Abdulaziz
Najlaa H. M. Mohamed
UQCV
29
0
0
31 Oct 2022
DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep Learning
Siqi Xu
Lin Liu
Zhong Liu
CML
MedIm
67
9
0
10 Oct 2022
Adaptive deep learning for nonlinear time series models
Daisuke Kurisu
Riku Fukami
Yuta Koike
AI4TS
58
6
0
06 Jul 2022
On the inability of Gaussian process regression to optimally learn compositional functions
M. Giordano
Kolyan Ray
Johannes Schmidt-Hieber
116
13
0
16 May 2022
Drift estimation for a multi-dimensional diffusion process using deep neural networks
Akihiro Oga
Yuta Koike
DiffM
54
6
0
26 Dec 2021
Nonconvex sparse regularization for deep neural networks and its optimality
Ilsang Ohn
Yongdai Kim
61
19
0
26 Mar 2020
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