Multi Domain Learning
Related Papers
Multi-Domain Learning: When Do Domains Matter?
We present a systematic analysis of exist- ing multi-domain learning approaches with re- spect to two questions. First, many multi- domain learning algorithms resemble ensem- ble learning algorithms. (1) Are …...
Automatic Domain Partitioning for Multi-Domain Learning
Multi-Domain learning (MDL) assumes that the domain labels in the dataset are known. However, when there are multiple metadata at- tributes available, it is not always straightfor- ward to select …...
Modeling the Use of Graffiti Style Features to Signal Social Relations within a Multi-Domain Learning Paradigm
In this paper, we present a series of experiments in which we analyze the usage of graffiti style features for signaling personal gang identification in a large, online street gangs …...
Semi-supervised Stochastic Multi-Domain Learning using Variational Inference
AbstractSupervised models of NLP rely on large collections of text which closely resemble the intended testing setting. Unfortunately matching text is often not available in sufficient quantity, and moreover, within …...