![Loading...](https://link.springer.com/static/c4a417b97a76cc2980e3c25e2271af3129e08bbe/images/pdf-preview/spacer.gif)
-
Chapter and Conference Paper
Impact of Fidelity and Robustness of Machine Learning Explanations on User Trust
EXplainable machine learning (XML) has recently emerged as a promising approach to address the inherent opacity of machine learning (ML) systems by providing insights into their reasoning processes. This paper...
-
Chapter and Conference Paper
Are Graph Neural Network Explainers Robust to Graph Noises?
With the rapid deployment of graph neural networks (GNNs) based techniques in a wide range of applications such as link prediction, community detection, and node classification, the explainability of GNNs beco...
-
Chapter and Conference Paper
Does a Compromise on Fairness Exist in Using AI Models?
Artificial Intelligence (AI) has been increasingly used to assist decision making in different domains. Multiple parties are usually affected by decisions in decision making, e.g. decision-maker and people aff...
-
Chapter and Conference Paper
A Hip Active Lower Limb Support Exoskeleton for Load Bearing Sit-To-Stand Transfer
Sit-to-stand (STS) transfer is a basic and important motion function in daily living. Most currently-existing studies focus on movement assistance for patients who lost mobility or have impaired their muscle s...
-
Chapter and Conference Paper
QoE and Reliability-Aware Task Scheduling for Multi-user Mobile-Edge Computing
Mobile-edge computing (MEC) has become a popular research topic from both academia and industry since it can alleviate the computation and power limitations of mobile devices by offloading computation-intensiv...
-
Chapter and Conference Paper
A Complex Attacks Recognition Method in Wireless Intrusion Detection System
During recent years, the challenge faced by wireless network security is getting severe with the rapid development of internet. However, due to the defects of wireless communication protocol and difference amo...
-
Chapter and Conference Paper
An Effective Feature Selection Method for Text Categorization
Feature selection is an efficient strategy to reduce the dimensionality of data and removing the noise in text categorization. However, most feature selection methods aim to remove non-informative features bas...