Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
The proliferation of heterogeneous devices and diverse networking technologies demands flexible models to guarantee the quality-of-service(QoS) at the application session level, ...
In the last decade there has been an explosion of interest in mining time series data. Literally hundreds of papers have introduced new algorithms to index, classify, cluster and s...
In previous work, we proposed a modal fragment of the situation calculus called ES, which fully captures Reiter’s basic action theories. ES also has epistemic features, includin...
Recent years have seen growth in the number of algorithms designed to solve challenging simulation-based nonlinear optimization problems. One such algorithm is the Trust-Region Par...