Multiclass classification for multidimensional functional data through deep neural networks
From MaRDI portal
Publication:6200908
DOI10.1214/24-ejs2229arXiv2305.13349OpenAlexW4392741981MaRDI QIDQ6200908
Publication date: 25 March 2024
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2305.13349
rate of convergencefunctional data analysismulticlass classificationdeep neural networksmultidimensional functional data
Nonparametric regression and quantile regression (62G08) Nonparametric robustness (62G35) Nonparametric estimation (62G05)
Cites Work
- Unnamed Item
- An extension of Fisher's discriminant analysis for stochastic processes
- Globally robust inference for the location and simple linear regression models
- Smooth discrimination analysis
- Bayesian classification of multiclass functional data
- Tensor product space ANOVA models.
- Optimal aggregation of classifiers in statistical learning.
- Convergence rates of deep ReLU networks for multiclass classification
- Nonparametric regression using deep neural networks with ReLU activation function
- On deep learning as a remedy for the curse of dimensionality in nonparametric regression
- Functional data analysis.
- Partially functional linear regression in high dimensions
- Componentwise classification and clustering of functional data
- Penalized Classification using Fisher’s Linear Discriminant
- On the Use of Reproducing Kernel Hilbert Spaces in Functional Classification
- Multiclass Sparse Discriminant Analysis
- High Dimensional Linear Discriminant Analysis: Optimality, Adaptive Algorithm and Missing Data
- OUP accepted manuscript
- Classification Using Censored Functional Data
- On Properties of Functional Principal Components Analysis
- Achieving near Perfect Classification for Functional Data
- Fast convergence rates of deep neural networks for classification
This page was built for publication: Multiclass classification for multidimensional functional data through deep neural networks