90 citations · 141 across the 11 of their papers we have counts for
Showing 2019Show all
3 papers · 1 filter
cs.LG2019★ 3 cited
A Survey of Techniques All Classifiers Can Learn from Deep Networks: Models, Optimizations, and Regularization
Alireza Ghods, Diane J Cook
Deep neural networks have introduced novel and useful tools to the machine learning community. Other types of classifiers can potentially make use of these tools as well to improve…
cs.LG2019★ 1 cited
Multi-Purposing Domain Adaptation Discriminators for Pseudo Labeling Confidence
Garrett Wilson, Diane J. Cook
Often domain adaptation is performed using a discriminator (domain classifier) to learn domain-invariant feature representations so that a classifier trained on labeled source data…
cs.LG2019★ 5 cited
Activity2Vec: Learning ADL Embeddings from Sensor Data with a Sequence-to-Sequence Model
Alireza Ghods, Diane J. Cook
Recognizing activities of daily living (ADLs) plays an essential role in analyzing human health and behavior. The widespread availability of sensors implanted in homes, smartphones…