Traffic flow forecasting or prediction plays an important role in the traffic control and
management of a city. Existing works mostly train a model using the traffic flow data of a city …

Most existing unsupervised active learning methods aim at minimizing the data
reconstruction loss by using the linear models to choose representative samples for …

As a machine learning paradigm, multi-task learning (MTL) attracts increasing attention
recently. It can improve the overall performance by exploiting the correlation among different …

Physical signs of patients indicate crucial evidence for diagnosing both location and nature
of the disease, where there is a sequential relationship between the two tasks. Thus their …

Multi-task learning (MTL) is an active field in deep learning in which we train a model to
jointly learn multiple tasks by exploiting relationships between the tasks. It has been shown …

Online healthcare consultation offers people a convenient way to consult doctors. In this
paper, we aim at building a generative dialog system for Chinese healthcare consultation …

多任务学**通过任务间的知识共享提升多个关联任务的泛化性能ꎮ 多任务学**领域的大多数
方法通过设置先验性的知识共享结构来定义任务间的关系ꎬ 这些知识共享结构可能使任务不能 …

Data heterogeneity such as task heterogeneity, view heterogeneity, and instance
heterogeneity often co-exist in many real-world applications including insider threat …