Search Results for author:
Found 2 papers, 2 papers with code
Slot Self-Attentive Dialogue State Tracking
Then a stacked slot self-attention is applied on these features to learn the correlations among slots.
Auto-weighted Robust Federated Learning with Corrupted Data Sources
In this paper, we address this challenge by proposing Auto-weighted Robust Federated Learning (arfl), a novel approach that jointly learns the global model and the weights of local updates to provide robustness against corrupted data sources.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
