Deep networks often possess a vast number of parameters, and their significant redundancy
in parameterization has become a widely-recognized property. This presents significant …

With increasingly explored ideologies and technologies for potential applications of artificial
intelligence (AI) in oncology, we here describe a holistic and structured concept termed …

Renewable wind power accounts for an increasing proportion of the smart grid nowadays.
The intermittent and fluctuating nature of wind renders wind power forecasting important …

Compressive learning (CL) is an emerging framework that integrates signal acquisition via
compressed sensing (CS) and machine learning for inference tasks directly on a small …

Reliable and accurate renewable energy forecasting (REF) has substantial impact on
society by helping with daily planning and mitigating the instability of power system …

Sketch-photo recognition is a cross-modal matching problem whose query sets are sketch
images drawn by artists or amateurs. Due to the significant modality difference between the …

Matching hand-drawn sketches with photos (aka sketch-photo recognition or re-
identification) faces the information asymmetry challenge due to the abstract nature of the …

Aspect-based sentiment analysis (ABSA) task consists of three typical subtasks: aspect term
extraction, opinion term extraction, and sentiment polarity classification. These three …

Pre-trained language models (PrLMs) have demonstrated superior performance due to their
strong ability to learn universal language representations from self-supervised pre-training …

Pickup and delivery problems with late penalties can be adopted to model a wide range of
practical situations in the field of transportation and logistics. However, the restrictions on the …