Collecting well-resolved empirical trophic networks requires significant time, money and expertise, yet we are still lacking knowledge on how sampling effort bias impact the estimation of network structure. Filling this gap is a critical first step towards creating accurate representations ecological for teasing apart compared to evolutionary processes that known create spatio-temporal variatio...

Representation learning approaches require a massive amount of discriminative training data, which is unavailable in many scenarios, such as healthcare, smart city, and education. In practice, people refer to crowdsourcing get annotated labels. However, due issues like data privacy, budget limitation, shortage domain-specific annotators, the number crowdsourced labels still very limited. Moreov...