My knowledge of the broader machine learning and neuroscience fields is limited, and I strongly suspect that there are connections to other topics out there – perhaps some that have already been studied, and perhaps some which have yet to be. For example, there are probably interesting connections between interpretability and dataset distillation (Wang et al., 2018). I’m just not sure what they are yet.
The dataset condensation (distillation) may be seen as the global explanation of the training dataset. And, we could also utilize DC to extract some spurious correlations like backdoor triggers. We made a naive attempt in this direction: https://openreview.net/forum?id=ix3UDwIN5E .
The dataset condensation (distillation) may be seen as the global explanation of the training dataset. And, we could also utilize DC to extract some spurious correlations like backdoor triggers. We made a naive attempt in this direction: https://openreview.net/forum?id=ix3UDwIN5E .