Learning Multiple Quantiles With Neural Networks
From MaRDI portal
Publication:5066505
DOI10.1080/10618600.2021.1909601OpenAlexW3149414568MaRDI QIDQ5066505
Yongdai Kim, Jason Sang Hun Lee, Sang Jun Moon, Jong-June Jeon
Publication date: 29 March 2022
Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10618600.2021.1909601
quantile regressionfeed-forward neural networkinterior point algorithmdeep learningprojected gradient algorithm
Related Items
On data-driven chance constraint learning for mixed-integer optimization problems, Estimation of extreme quantiles from heavy-tailed distributions with neural networks
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Robust neural network with applications to credit portfolio data analysis
- On the convergence properties of the projected gradient method for convex optimization
- Composite quantile regression and the oracle model selection theory
- New normalization methods using support vector machine quantile regression approach in microarray analysis
- Regularized simultaneous model selection in multiple quantiles regression
- On the projected subgradient method for nonsmooth convex optimization in a Hilbert space
- On spline estimators and prediction intervals in nonparametric regression.
- Quantile regression for longitudinal data
- Noncrossing quantile regression curve estimation
- Quantile and Probability Curves Without Crossing
- Local Linear Quantile Regression
- Regression Quantiles
- Quantile smoothing splines
- Methods for Estimating a Conditional Distribution Function
- A Recurrent Neural Network for Nonlinear Convex Optimization Subject to Nonlinear Inequality Constraints
- Local Composite Quantile Regression Smoothing: An Efficient and Safe Alternative to Local Polynomial Regression
- An Extended Projection Neural Network for Constrained Optimization
