Deep Nonparametric Regression on Approximate Manifolds: Non-Asymptotic
Error Bounds with Polynomial Prefactors

Deep Nonparametric Regression on Approximate Manifolds: Non-Asymptotic Error Bounds with Polynomial Prefactors

14 April 2021

Yuling Jiao

Papers citing "Deep Nonparametric Regression on Approximate Manifolds: Non-Asymptotic Error Bounds with Polynomial Prefactors"

17 / 17 papers shown

Title
Wasserstein Distributionally Robust Nonparametric Regression Changyu Liu Yuling Jiao Junhui Wang Jian Huang OOD 31 0 0 12 May 2025
Learning Guarantee of Reward Modeling Using Deep Neural Networks Yuanhang Luo Yeheng Ge Ruijian Han Guohao Shen 31 0 0 10 May 2025
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models Jialong Jiang Wenkang Hu Jian Huang Yuling Jiao Xu Liu DiffM 50 0 0 08 May 2025
Deep learning with missing data Tianyi Ma Tengyao Wang R. Samworth 61 0 0 21 Apr 2025
Inferring Outcome Means of Exponential Family Distributions Estimated by Deep Neural Networks Xuran Meng Yi Li BDL 32 0 0 12 Apr 2025
Learning with Noisy Labels: the Exploration of Error Bounds in Classification Haixia Liu Boxiao Li Can Yang Yang Wang 33 0 0 28 Jan 2025
Deep Transfer Learning: Model Framework and Error Analysis Yuling Jiao Huazhen Lin Yuchen Luo Jerry Zhijian Yang 44 1 0 12 Oct 2024
Deep non-parametric logistic model with case-control data and external summary information Hengchao Shi M. Zheng Wen Yu 25 0 0 03 Sep 2024
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 3 0 05 Jun 2024
Model Free Prediction with Uncertainty Assessment Yuling Jiao Lican Kang Jin Liu Heng Peng Heng Zuo DiffM 34 0 0 21 May 2024
Generative adversarial learning with optimal input dimension and its adaptive generator architecture Zhiyao Tan Ling Zhou Huazhen Lin GAN 34 0 0 06 May 2024
Deep neural network approximation of composite functions without the curse of dimensionality Adrian Riekert 22 0 0 12 Apr 2023
Rates of convergence for nonparametric estimation of singular distributions using generative adversarial networks Minwoo Chae GAN 32 4 0 07 Feb 2022
The Intrinsic Dimension of Images and Its Impact on Learning Phillip E. Pope Chen Zhu Ahmed Abdelkader Micah Goldblum Tom Goldstein 197 260 0 18 Apr 2021
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth Zuowei Shen Haizhao Yang Shijun Zhang 101 115 0 28 Feb 2021
Benefits of depth in neural networks Matus Telgarsky 136 602 0 14 Feb 2016