The measurement of an electric field is of great significance for applications such as online monitoring and fault diagnosis in the ubiquitous power Internet of Things (UPIoT), meteorological monit…
Recently, a popular line of research in face recognition is adopting margins in the well-established softmax loss function to maximize class separability. In this paper, we first introduce an Addit…
DNA methylation (DNAm) has been suggested to play a critical role in post-traumatic stress disorder (PTSD), through mediating the relationship between trauma and PTSD. However, this underlying mech…
An optimal dynamic treatment regime (DTR) consists of a sequence of decision rules in maximizing long-term benefits, which is applicable for chronic diseases such as HIV infection or cancer. In thi…
Deep reinforcement learning (DRL) has been introduced to the routing and spectrum assignment (RSA) of elastic optical networks (EONs) where the RSA policies are learnt during the interaction of a D…
In the task of pedestrian trajectory prediction, social interaction could be one of the most complicated factors since it is difficult to be interpreted through simple rules. Recent studies have sh…
k -means method using Lloyd heuristic is a traditional clustering method which has played a key role in multiple downstream tasks of machine learning because of its simplicity. However, Lloyd heuri…
We propose a novel deep visual odometry (VO) method that considers global information by selecting memory and refining poses. Existing learning-based methods take the VO task as a pure tracking pro…
For multisource data, blocks of variable information from certain sources are likely missing. Existing methods for handling missing data do not take structures of block-wise missing data into consi…
In this article, we propose a heterogeneous modeling framework which achieves individual-wise feature selection and heterogeneous covariates’ effects subgrouping simultaneously. In contrast to co…