User response prediction is a crucial component for personalized information retrieval and
filtering scenarios, such as recommender system and web search. The data in user …

The increasing use of electronic forms of communication presents new opportunities in the
study of mental health, including the ability to investigate the manifestations of psychiatric …

Hyperspectral unmixing is an important problem for remotely sensed data interpretation. It
amounts at estimating the spectral signatures of the pure spectral constituents in the scene …

Attribute-aware CF models aim at rating prediction given not only the historical rating given
by users to items but also the information associated with users (eg, age), items (eg, price) …

Multi-task learning has been widely applied in computational vision, natural language
processing and other fields, which has achieved well performance. In recent years, a lot of …

Continuous mid-air hand gesture recognition based on captured hand pose streams is
fundamental for human-computer interaction, particularly in AR/VR. However, many of the …

Link prediction and node classification are two important downstream tasks of network
representation learning. Existing methods have achieved acceptable results but they …

In the context of supervised tensor learning, preserving the structural information and
exploiting the discriminative nonlinear relationships of tensor data are crucial for improving …

Factorization machines are a generic supervised method for a wide range of tasks in the
field of artificial intelligence, such as prediction, inference, etc., which can effectively model …

The state-of-the-art multitask multiview (MTMV) learning tackles a scenario where multiple
tasks are related to each other via multiple shared feature views. However, in many real …