The recent advanced deep learning techniques have shown the promising re...
Time series data is prevalent in a wide variety of real-world applicatio...
In recent years, Graph Convolutional Networks (GCNs) show competitive
pe...
Recent advancements in audio event classification often ignore the struc...
Nowadays, Internet is a primary source of attaining health information.
...
Multivariate time series (MTS) forecasting is widely used in various dom...
Selecting important variables and learning predictive models from
high-d...
We consider the problem of learning predictive models from longitudinal ...
Real-world graph applications, such as advertisements and product
recomm...
Graph neural networks (GNNs) are widely used in many applications. Howev...
Hybrid analog-digital precoding is challenging for broadband millimeter-...
We explore the use of a knowledge graphs, that capture general or common...
Real-world social networks and digital platforms are comprised of indivi...
Hybrid precoding design can be challenging for broadband millimeter-wave...
Millimeter-wave (mmWave) communication is considered as an indispensable...
Many machine learning, statistical inference, and portfolio optimization...