The field of transfer learning is undergoing a significant shift with th...
We study task-agnostic continual reinforcement learning (TACRL) in which...
Modularity is a compelling solution to continual learning (CL), the prob...
Finding neural network weights that generalize well from small datasets ...
The field of Continual Learning (CL) seeks to develop algorithms that
ac...
Classical machine learning algorithms often assume that the data are dra...
Explainability for machine learning models has gained considerable atten...
Progress in the field of machine learning has been fueled by the introdu...
In the last few years, we have witnessed a renewed and fast-growing inte...
Learning from non-stationary data remains a great challenge for machine
...
We introduce and study the problem of Online Continual Compression, wher...
Continual learning, the setting where a learning agent is faced with a n...
Generating high-quality text with sufficient diversity is essential for ...