3 citations · 4 across the 3 of their papers we have counts for
3 papers
stat.ML2021
Non-stationary Gaussian process discriminant analysis with variable selection for high-dimensional functional data
W Yu, S Wade, H D Bondell +1
High-dimensional classification and feature selection tasks are ubiquitous with the recent advancement in data acquisition technology. In several application areas such as biology,…
stat.ML2020★ 1 cited
Nonparametric Conditional Density Estimation In A Deep Learning Framework For Short-Term Forecasting
David B. Huberman, Brian J. Reich, Howard D. Bondell
Short-term forecasting is an important tool in understanding environmental processes. In this paper, we incorporate machine learning algorithms into a conditional distribution esti…
stat.ML2019★ 3 cited
Deep Distribution Regression
Rui Li, Howard D. Bondell, Brian J. Reich
Due to their flexibility and predictive performance, machine-learning based regression methods have become an important tool for predictive modeling and forecasting. However, most…