Browse by Subject "machine learning"
Now showing items 36-38 of 38
(2008-07)The aim of transfer learning is to reduce sample complexity required to solve a learning task by using information gained from solving related tasks. Transfer learning has in general been motivated by the observation that ...
(2012-05-22)Current analyses of groundwater flow and transport typically rely on a physically-based model (PBM), which is inherently subject to error and uncertainty from multiple sources including model structural error, parameter ...
Using machine learning models to interpret disciplinary styles of metadiscourse in dissertation abstracts (iSchools, 2013-02)This paper presents the results of a study of disciplinary stylistic differences among dissertation abstracts from physics, psychology, and philosophy. Based on differences in relative frequencies of metadiscourse terms ...