In this work, we develop an Aligned Entropic Reproducing Kernel (AERK) f...
In this paper, we propose a novel graph kernel, namely the Quantum-based...
In this work, we propose a family of novel quantum kernels, namely the
H...
To alleviate the challenges of building Knowledge Graphs (KG) from scrat...
Event extraction, the technology that aims to automatically get the
stru...
Joint-event-extraction, which extracts structural information (i.e., ent...
In this paper, we develop a new graph kernel, namely the Hierarchical
Tr...
We formalize networks with evolving structures as temporal networks and
...
In this work, we develop a novel framework to measure the similarity bet...
Counterfactual thinking describes a psychological phenomenon that people...
We develop a novel method for measuring the similarity between complete
...
In this paper, we develop a novel Aligned-Spatial Graph Convolutional Ne...
Feature selection has been proven a powerful preprocessing step for
high...
In this paper, we develop a new aligned vertex convolutional network mod...
Most recent works model the market structure of the stock market as a
co...
Feature selection can efficiently identify the most informative features...
In this paper, we develop a new Quantum Spatial Graph Convolutional Neur...