Node classification is a substantial problem in graph-based fraud detect...
Learning the change of statistical dependencies between random variables...
Because tensor data appear more and more frequently in various scientifi...
Motivated by applications in various scientific fields having demand of
...
We consider the problem of including additional knowledge in estimating
...
We focus on the problem of estimating the change in the dependency struc...
String Kernel (SK) techniques, especially those using gapped k-mers as
f...
Recent studies have shown that deep neural networks (DNN) are vulnerable...
Estimating multiple sparse Gaussian Graphical Models (sGGMs) jointly for...
Most machine learning classifiers, including deep neural networks, are
v...
Deep neural network (DNN) models have recently obtained state-of-the-art...
Identifying context-specific entity networks from aggregated data is an
...