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04/06/2023
Multi-label classification of open-ended questions with BERT
Open-ended questions in surveys are valuable because they do not constra...
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09/13/2022
Automated classification for open-ended questions with BERT
Manual coding of text data from open-ended questions into different cate...
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02/15/2021
One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes
Increasingly large datasets are rapidly driving up the computational cos...
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10/31/2020
Optimal 1-NN Prototypes for Pathological Geometries
Using prototype methods to reduce the size of training datasets can dras...
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09/19/2020
SecDD: Efficient and Secure Method for Remotely Training Neural Networks
We leverage what are typically considered the worst qualities of deep le...
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09/17/2020
'Less Than One'-Shot Learning: Learning N Classes From M<N Samples
Deep neural networks require large training sets but suffer from high co...
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10/06/2019
Improving Dataset Distillation
Dataset distillation is a method for reducing dataset sizes: the goal is...
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04/10/2019
Deep Learning for System Trace Restoration
Most real-world datasets, and particularly those collected from physical...
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02/15/2017
