3 accepted papers
The recent flourish of deep learning on various tasks is largely accredited to the rich and high-quality labeled data. Nonetheless, collecting sufficient labeled samples is not very practical for many real applications. Few-shot Learning (FSL) provides a promising solution that allows a model to lea…
Mode decomposition methods are the current workhorse for the analysis of non-stationary signals. However, current attempts at these methods mainly focus on improving accuracy, leaving computational efficiency untouched. To this end, we leverage the neural mode decomposition technique and propose an…
We study the problem of object reconstruction in a multi-agent collaboration scenario. Specifically, we focus on the reconstruction of specific goals through several cooperative agents equipped with vision sensors to achieve higher efficiency than single agents. Our main insight is that a complete 3…