Search Results for author:
Found 2 papers, 0 papers with code
Transfer Learning via Latent Dependency Factor for Estimating PM 2.5
We recognize this transfer problem as spatial transfer learning and propose a new feature named Latent Dependency Factor (LDF) that captures spatial and semantic dependencies of both domains and is subsequently added to the datasets.
ISTRBoost: Importance Sampling Transfer Regression using Boosting
Our methodology,~\us{}, is a boosting and random-forest based ensemble methodology that utilizes importance sampling to reduce the skewness due to the source dataset.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
