On Target Shift in Adversarial Domain Adaptation

no code implementations • 15 Mar 2019 • Yitong Li, Michael Murias, Samantha Major, Geraldine Dawson, David E. Carlson

In this work, we propose a method called Domain Adversarial nets for Target Shift (DATS) to address label shift while learning a domain invariant representation.

Domain Adaptation

Targeting EEG/LFP Synchrony with Neural Nets

no code implementations • NeurIPS 2017 • Yitong Li, Michael Murias, Samantha Major, Geraldine Dawson, Kafui Dzirasa, Lawrence Carin, David E. Carlson

We consider the analysis of Electroencephalography (EEG) and Local Field Potential (LFP) datasets, which are “big” in terms of the size of recorded data but rarely have sufficient labels required to train complex models (e. g., conventional deep learning methods).

EEG