3 accepted papers
Causal discovery on event sequences holds a pivotal significance across domains such as healthcare, finance, and industrial systems. The crux of this endeavor lies in unraveling causal structures among event types, typically portrayed as directed acyclic graphs (DAGs). Nonetheless, prevailing method…
The recovery of autonomous underwater vehicles (AUVs) has been a challenging mission due to the limited localization accuracy and movement capability of the AUVs. To overcome these limitations, we propose a novel design of a deployable underwater robot (DUR) for the recovery mission. Utilizing the o…
Natural language understanding (NLU) aims at identifying user intent and extracting semantic slots. This requires sufficient annotating data to get considerable performance in real-world situations. Active learning (AL) has been well-studied to decrease the needed amount of the annotating data and s…