Active Learning (AL) is a human-in-the-loop framework to interactively a...
A salient characteristic of large pre-trained language models (PTLMs) is...
Deep neural networks have seen great success in recent years; however,
t...
Continual learning (CL) aims to develop techniques by which a single mod...
A critical bottleneck in supervised machine learning is the need for lar...
Active learning has proven to be useful for minimizing labeling costs by...
Semi-supervised learning (SSL) algorithms have had great success in rece...
Large scale machine learning and deep models are extremely data-hungry.
...
Model-Agnostic Meta-Learning (MAML) is a popular gradient-based meta-lea...
The paradigm of data programming <cit.> has shown a lot of
promise in us...