With advances in technology, high volumes of a wide variety of valuable data of different
veracity can be easily collected or generated at a high velocity in the current era of big data …

In this paper, we focus on designing an online credit card fraud detection framework with big
data technologies, by which we want to achieve three major goals: 1) the ability to fuse …

The challenge of scalability has always been a focus on Machine Learning research, where
improved algorithms and new techniques are proposed in a constant basis to deal with more …

Edge computing extends traditional cloud services to the edge of the network, and the highly
dynamic and heterogeneous environment at the edge of the network makes the network …

Bagging has attracted much attention due to its simple implementation and the popularity of
bootstrapping. By learning diverse classifiers from resampled datasets and averaging the …

Over recent decades, the rapid growth in data makes ever more urgent the quest for highly
scalable Bayesian networks that have better classification performance and expressivity …

Effectively predicting the spatial distribution of oil and gas contributes to delineating
promising target areas for further exploration. Determining the location of hydrocarbon is a …

The finite state transducer (FST) approach has been widely used as an effective and flexible
framework for speech systems. In this framework, a speech recognizer is represented as the …

To mitigate the negative effect of classification bias caused by overfitting, semi-naive
Bayesian techniques seek to mine the implicit dependency relationships in unlabeled …