Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality

18 October 2018

Papers citing "Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality"

50 / 53 papers shown

Title
Super-fast rates of convergence for Neural Networks Classifiers under the Hard Margin Condition Nathanael Tepakbong Ding-Xuan Zhou Xiang Zhou 46 0 0 13 May 2025
Higher Order Approximation Rates for ReLU CNNs in Korobov Spaces Yuwen Li Guozhi Zhang 46 1 0 20 Jan 2025
On the optimal approximation of Sobolev and Besov functions using deep ReLU neural networks Yunfei Yang 62 2 0 02 Sep 2024
Posterior and variational inference for deep neural networks with heavy-tailed weights Ismael Castillo Paul Egels BDL 60 4 0 05 Jun 2024
Learning with Norm Constrained, Over-parameterized, Two-layer Neural Networks Fanghui Liu L. Dadi V. Cevher 85 2 0 29 Apr 2024
Approximation Rates and VC-Dimension Bounds for (P)ReLU MLP Mixture of Experts Anastasis Kratsios Haitz Sáez de Ocáriz Borde Takashi Furuya Marc T. Law MoE 41 1 0 05 Feb 2024
Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning Hao Liu Biraj Dahal Rongjie Lai Wenjing Liao AI4CE 34 5 0 19 Jan 2024
Nonlinear functional regression by functional deep neural network with kernel embedding Zhongjie Shi Jun Fan Linhao Song Ding-Xuan Zhou Johan A. K. Suykens 65 5 0 05 Jan 2024
Neural Network Approximation for Pessimistic Offline Reinforcement Learning Di Wu Yuling Jiao Li Shen Haizhao Yang Xiliang Lu OffRL 29 1 0 19 Dec 2023
Statistical Spatially Inhomogeneous Diffusion Inference Yinuo Ren Yiping Lu Lexing Ying Grant M. Rotskoff 22 2 0 10 Dec 2023
Analysis of the expected $L_2$ error of an over-parametrized deep neural network estimate learned by gradient descent without regularization Selina Drews Michael Kohler 38 3 0 24 Nov 2023
Statistical learning by sparse deep neural networks Felix Abramovich BDL 26 1 0 15 Nov 2023
Fitted Value Iteration Methods for Bicausal Optimal Transport Erhan Bayraktar Bingyan Han OT 37 6 0 22 Jun 2023
Pairwise Ranking with Gaussian Kernels Guanhang Lei Lei Shi 32 2 0 06 Apr 2023
Deep Operator Learning Lessens the Curse of Dimensionality for PDEs Ke Chen Chunmei Wang Haizhao Yang AI4CE 24 13 0 28 Jan 2023
Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions Ido Ben-Shaul Tomer Galanti S. Dekel 31 3 0 11 Jan 2023
Smooth Sailing: Improving Active Learning for Pre-trained Language Models with Representation Smoothness Analysis Josip Jukić Jan Snajder 16 5 0 20 Dec 2022
A Review of Off-Policy Evaluation in Reinforcement Learning Masatoshi Uehara C. Shi Nathan Kallus OffRL 36 69 0 13 Dec 2022
Analysis of the rate of convergence of an over-parametrized deep neural network estimate learned by gradient descent Michael Kohler A. Krzyżak 32 10 0 04 Oct 2022
Approximation results for Gradient Descent trained Shallow Neural Networks in $1d$ R. Gentile G. Welper ODL 56 6 0 17 Sep 2022
On the universal consistency of an over-parametrized deep neural network estimate learned by gradient descent Selina Drews Michael Kohler 30 14 0 30 Aug 2022
Deep Neural Network Classifier for Multi-dimensional Functional Data Shuoyang Wang Guanqun Cao Zuofeng Shang 34 12 0 17 May 2022
On the inability of Gaussian process regression to optimally learn compositional functions M. Giordano Kolyan Ray Johannes Schmidt-Hieber 53 12 0 16 May 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation Jimmy Ba Murat A. Erdogdu Taiji Suzuki Zhichao Wang Denny Wu Greg Yang MLT 42 121 0 03 May 2022
Uncertainty Quantification for nonparametric regression using Empirical Bayesian neural networks Stefan Franssen Botond Szabó BDL UQCV 21 4 0 27 Apr 2022
Qualitative neural network approximation over R and C: Elementary proofs for analytic and polynomial activation Josiah Park Stephan Wojtowytsch 26 1 0 25 Mar 2022
How do noise tails impact on deep ReLU networks? Jianqing Fan Yihong Gu Wen-Xin Zhou ODL 41 13 0 20 Mar 2022
SLIDE: a surrogate fairness constraint to ensure fairness consistency Kunwoong Kim Ilsang Ohn Sara Kim Yongdai Kim 35 4 0 07 Feb 2022
Interplay between depth of neural networks and locality of target functions Takashi Mori Masakuni Ueda 25 0 0 28 Jan 2022
Convex Analysis of the Mean Field Langevin Dynamics Atsushi Nitanda Denny Wu Taiji Suzuki MLT 77 64 0 25 Jan 2022
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces Hao Liu Haizhao Yang Minshuo Chen T. Zhao Wenjing Liao 32 36 0 01 Jan 2022
Drift estimation for a multi-dimensional diffusion process using deep neural networks Akihiro Oga Yuta Koike DiffM 21 5 0 26 Dec 2021
Deep Network Approximation in Terms of Intrinsic Parameters Zuowei Shen Haizhao Yang Shijun Zhang 21 9 0 15 Nov 2021
Near-Minimax Optimal Estimation With Shallow ReLU Neural Networks Rahul Parhi Robert D. Nowak 58 38 0 18 Sep 2021
Robust Nonparametric Regression with Deep Neural Networks Guohao Shen Yuling Jiao Yuanyuan Lin Jian Huang OOD 33 13 0 21 Jul 2021
Theory of Deep Convolutional Neural Networks III: Approximating Radial Functions Tong Mao Zhongjie Shi Ding-Xuan Zhou 16 33 0 02 Jul 2021
Rejoinder: On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning Lin Liu Rajarshi Mukherjee J. M. Robins CML 33 16 0 07 Aug 2020
Phase Transitions in Rate Distortion Theory and Deep Learning Philipp Grohs Andreas Klotz F. Voigtlaender 14 7 0 03 Aug 2020
Approximation of Smoothness Classes by Deep Rectifier Networks Mazen Ali A. Nouy 17 9 0 30 Jul 2020
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 16 51 0 09 Jul 2020
Learning with tree tensor networks: complexity estimates and model selection Bertrand Michel A. Nouy 15 14 0 02 Jul 2020
When Does Preconditioning Help or Hurt Generalization? S. Amari Jimmy Ba Roger C. Grosse Xuechen Li Atsushi Nitanda Taiji Suzuki Denny Wu Ji Xu 36 32 0 18 Jun 2020
Approximation in shift-invariant spaces with deep ReLU neural networks Yunfei Yang Zhen Li Yang Wang 34 14 0 25 May 2020
A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth Yiping Lu Chao Ma Yulong Lu Jianfeng Lu Lexing Ying MLT 39 78 0 11 Mar 2020
Deep Network Approximation for Smooth Functions Jianfeng Lu Zuowei Shen Haizhao Yang Shijun Zhang 67 247 0 09 Jan 2020
Variational Physics-Informed Neural Networks For Solving Partial Differential Equations E. Kharazmi Z. Zhang George Karniadakis 24 238 0 27 Nov 2019
The Local Elasticity of Neural Networks Hangfeng He Weijie J. Su 40 44 0 15 Oct 2019
Deep Network Approximation Characterized by Number of Neurons Zuowei Shen Haizhao Yang Shijun Zhang 23 182 0 13 Jun 2019
Nonlinear Approximation via Compositions Zuowei Shen Haizhao Yang Shijun Zhang 26 92 0 26 Feb 2019
Nonparametric Density Estimation & Convergence Rates for GANs under Besov IPM Losses Ananya Uppal Shashank Singh Barnabás Póczós 30 52 0 09 Feb 2019