Consistency for Large Neural Networks: Regression and Classification
Fuente:
arXiv
Saved in:
| Main Authors: | Zhan, Haoran, Xia, Yingcun |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Consistency of Oblique Decision Tree and its Boosting and Random Forest
by: Zhan, Haoran, et al.
Published: (2022)
by: Zhan, Haoran, et al.
Published: (2022)
Learning Curves and Benign Overfitting of Spectral Algorithms in Large Dimensions
by: Lu, Weihao, et al.
Published: (2026)
by: Lu, Weihao, et al.
Published: (2026)
Online Quantile Regression for Nonparametric Additive Models
by: Zhan, Haoran
Published: (2026)
by: Zhan, Haoran
Published: (2026)
Non-asymptotic Properties of Generalized Mondrian Forests in Statistical Learning
by: Zhan, Haoran, et al.
Published: (2024)
by: Zhan, Haoran, et al.
Published: (2024)
Asymptotic Optimism for Tensor Regression Models with Applications to Neural Network Compression
by: Shi, Haoming, et al.
Published: (2026)
by: Shi, Haoming, et al.
Published: (2026)
Active Learning for Regression based on Wasserstein distance and GroupSort Neural Networks
by: Bobbia, Benjamin, et al.
Published: (2024)
by: Bobbia, Benjamin, et al.
Published: (2024)
The Adversarial Consistency of Surrogate Risks for Binary Classification
by: Frank, Natalie, et al.
Published: (2023)
by: Frank, Natalie, et al.
Published: (2023)
Plug-In Classification of Drift Functions in Diffusion Processes Using Neural Networks
by: Zhao, Yuzhen, et al.
Published: (2026)
by: Zhao, Yuzhen, et al.
Published: (2026)
Sharp Generalization for Nonparametric Regression in Interpolation Space by Over-Parameterized Neural Networks Trained with Preconditioned Gradient Descent and Early Stopping
by: Yang, Yingzhen, et al.
Published: (2024)
by: Yang, Yingzhen, et al.
Published: (2024)
Debiased Regression for Root-N-Consistent Conditional Mean Estimation
by: Kato, Masahiro
Published: (2024)
by: Kato, Masahiro
Published: (2024)
Optimal Classification-based Anomaly Detection with Neural Networks: Theory and Practice
by: Zhou, Tian-Yi, et al.
Published: (2024)
by: Zhou, Tian-Yi, et al.
Published: (2024)
Approximation of RKHS Functionals by Neural Networks
by: Zhou, Tian-Yi, et al.
Published: (2024)
by: Zhou, Tian-Yi, et al.
Published: (2024)
Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm
by: Xia, Xintao, et al.
Published: (2024)
by: Xia, Xintao, et al.
Published: (2024)
Semi-supervised Fréchet Regression
by: Qiu, Rui, et al.
Published: (2024)
by: Qiu, Rui, et al.
Published: (2024)
Kernel Ridge Regression Inference
by: Singh, Rahul, et al.
Published: (2023)
by: Singh, Rahul, et al.
Published: (2023)
Phase Transitions for Feature Learning in Neural Networks
by: Montanari, Andrea, et al.
Published: (2026)
by: Montanari, Andrea, et al.
Published: (2026)
Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories
by: Zhang, Haobo, et al.
Published: (2024)
by: Zhang, Haobo, et al.
Published: (2024)
Affine Invariance in Continuous-Domain Convolutional Neural Networks
by: Mohaddes, Ali, et al.
Published: (2023)
by: Mohaddes, Ali, et al.
Published: (2023)
Can Bayesian Neural Networks Make Confident Predictions?
by: Fisher, Katharine, et al.
Published: (2025)
by: Fisher, Katharine, et al.
Published: (2025)
Tensor Product Neural Networks for Functional ANOVA Model
by: Park, Seokhun, et al.
Published: (2025)
by: Park, Seokhun, et al.
Published: (2025)
Dense ReLU Neural Networks for Temporal-spatial Model
by: Padilla, Carlos Misael Madrid, et al.
Published: (2024)
by: Padilla, Carlos Misael Madrid, et al.
Published: (2024)
Minimax Linear Regression under the Quantile Risk
by: Hanchi, Ayoub El, et al.
Published: (2024)
by: Hanchi, Ayoub El, et al.
Published: (2024)
Online and Offline Robust Multivariate Linear Regression
by: Godichon-Baggioni, Antoine, et al.
Published: (2024)
by: Godichon-Baggioni, Antoine, et al.
Published: (2024)
Exploring the Complexity of Deep Neural Networks through Functional Equivalence
by: Shen, Guohao
Published: (2023)
by: Shen, Guohao
Published: (2023)
Non-identifiability distinguishes Neural Networks among Parametric Models
by: Chatterjee, Sourav, et al.
Published: (2025)
by: Chatterjee, Sourav, et al.
Published: (2025)
Statistical Guarantees for Approximate Stationary Points of Shallow Neural Networks
by: Taheri, Mahsa, et al.
Published: (2022)
by: Taheri, Mahsa, et al.
Published: (2022)
Inference for Deep Neural Network Estimators in Generalized Nonparametric Models
by: Meng, Xuran, et al.
Published: (2025)
by: Meng, Xuran, et al.
Published: (2025)
Nonparametric Instrumental Variable Regression with Observed Covariates
by: Shen, Zikai, et al.
Published: (2025)
by: Shen, Zikai, et al.
Published: (2025)
Active Learning via Regression Beyond Realizability
by: Ganju, Atul, et al.
Published: (2025)
by: Ganju, Atul, et al.
Published: (2025)
Support Vector Regression: Risk Quadrangle Framework
by: Malandii, Anton, et al.
Published: (2022)
by: Malandii, Anton, et al.
Published: (2022)
Functional Linear Regression of Cumulative Distribution Functions
by: Zhang, Qian, et al.
Published: (2022)
by: Zhang, Qian, et al.
Published: (2022)
Sparse Max-Affine Regression
by: Kanj, Haitham, et al.
Published: (2024)
by: Kanj, Haitham, et al.
Published: (2024)
Adversarial Consistency and the Uniqueness of the Adversarial Bayes Classifier
by: Frank, Natalie S.
Published: (2024)
by: Frank, Natalie S.
Published: (2024)
Consistent support recovery for high-dimensional diffusions
by: Marushkevych, Dmytro, et al.
Published: (2025)
by: Marushkevych, Dmytro, et al.
Published: (2025)
Belted and Ensembled Neural Network for Linear and Nonlinear Sufficient Dimension Reduction
by: Tang, Yin, et al.
Published: (2024)
by: Tang, Yin, et al.
Published: (2024)
Upper Bounds for Local Learning Coefficients of Three-Layer Neural Networks
by: Kurumadani, Yuki
Published: (2026)
by: Kurumadani, Yuki
Published: (2026)
Generalization for Least Squares Regression With Simple Spiked Covariances
by: Li, Jiping, et al.
Published: (2024)
by: Li, Jiping, et al.
Published: (2024)
Minimax-optimal and Locally-adaptive Online Nonparametric Regression
by: Liautaud, Paul, et al.
Published: (2024)
by: Liautaud, Paul, et al.
Published: (2024)
Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps
by: Shi, Zhaoyang, et al.
Published: (2024)
by: Shi, Zhaoyang, et al.
Published: (2024)
Convex Regression in Multidimensions: Suboptimality of Least Squares Estimators
by: Kur, Gil, et al.
Published: (2020)
by: Kur, Gil, et al.
Published: (2020)
Similar Items
-
Consistency of Oblique Decision Tree and its Boosting and Random Forest
by: Zhan, Haoran, et al.
Published: (2022) -
Learning Curves and Benign Overfitting of Spectral Algorithms in Large Dimensions
by: Lu, Weihao, et al.
Published: (2026) -
Online Quantile Regression for Nonparametric Additive Models
by: Zhan, Haoran
Published: (2026) -
Non-asymptotic Properties of Generalized Mondrian Forests in Statistical Learning
by: Zhan, Haoran, et al.
Published: (2024) -
Asymptotic Optimism for Tensor Regression Models with Applications to Neural Network Compression
by: Shi, Haoming, et al.
Published: (2026)