In recent years, deep neural networks have achieved exciting results in a variety of tasks,
and many fields try to introduce neural network techniques. In mobile edge computing, there …

Traffic flow prediction has received extensive attention recently, since it is a key step to
prevent and mitigate traffic congestion in urban areas. However, most previous studies on …

Probabilistic time series forecasting aims at estimating future probabilistic distributions
based on given time series observations. It is a widespread challenge in various tasks, such …

With the growing number of competing Web services that provide similar functionality,
Quality-of-Service (QoS) prediction is becoming increasingly important for various QoS …

With the widespread deployment of various cloud computing and service-oriented systems,
there is a rapidly increasing demand for collaborative quality-of-service (QoS) prediction …

Nowadays, there are many Web services with similar functionality on the Internet. Users
consider Quality of Service (QoS) of the services to select the best service from among them …

Quality of service (QoS) has been mostly applied to represent non-functional properties of
web services and differentiate those with the same functionality. How to accurately predict …

Multivariate time series forecasting is an important yet challenging problem in machine
learning. Most existing approaches only forecast the series value of one future moment …

The proliferation of Web services makes it difficult for users to select the most appropriate
one among numerous functionally identical or similar service candidates. Quality-of-Service …

The high-precision QoS (quality of service) prediction is based on the comprehensive
perception of state information of users and services. However, the current QoS prediction …