Robust principal component analysis (RPCA) via decomposition into low-rank plus sparse
matrices offers a powerful framework for a large variety of applications such as image …

Document-level RE requires reading, inferring and aggregating over multiple sentences.
From our point of view, it is necessary for document-level RE to take advantage of multi …

Adverse selection (AS) is one of the significant causes of market failure worldwide. Analysis
and deep insights into the Australian life insurance market show the existence of adverse …

Off-policy learning has drawn huge attention in recommender systems (RS), which provides
an opportunity for reinforcement learning to abandon the expensive online training …

Much recent research has shed light on developing the relation-dependent but the content-
independent framework for social spammer detection. This is mainly because the relation …

Sinkhorn divergence has become a very popular metric to compare probability distributions
in optimal transport. However, most works resort to Sinkhorn divergence in Euclidean space …

Reinforcement learning has recently become an active topic in recommender system
research, where the logged data that records interactions between items and users …

Efficient communication is a promising way to achieve cooperation among agents in many
real-world scenarios. However, aimless and motiveless information sharing may not work or …

Underwriting is an important process in insurance and is concerned with accepting
individuals into insurance policy with tolerable claim risk. Underwriting is a tedious and labor …

Sequential recommendation leverages the temporal information of users' transactions as
transition dependencies for better inferring user preference, which has become increasingly …