In the recent years, Internet of things (IoT) is rising increasingly to become a big research
topic due to the billions of devices dispatched around the world. These devices are …

Exploiting machine learning techniques for analyzing programs has attracted much
attention. One key problem is how to represent code fragments well for follow-up analysis …

The tree structure is one of the most powerful structures for data organization. An efficient
learning framework for transforming tree-structured data into vectorial representations is …

In this paper, a multi-instance multi-label algorithm based on neural networks is proposed
for image classification. The proposed algorithm, termed multi-instance multi-label neural …

Image classification is a challenging problem of computer vision. Conventional image
classification methods use flat image features with fixed dimensions, which are extracted …

This paper proposes a novel supervised learning method for single-layer feedforward neural
networks. This approach uses an alternative objective function to that based on the MSE …

Natural language summaries of source codes are important during software development
and maintenance. Recently, deep learning based models have achieved good performance …

On a meta-learning process, the key is to build a reliable meta-training data set, which
requires the best model for a specific sample. In the other hand, the uncertainty of expected …

This paper presents a novel approach for recognizing human facial emotion in order to
further detect human suspicious behaviors. Instead of relying on relative poor representation …

This paper describes a novel structural approach to recognize the human facial features for
emotion recognition. Conventionally, features extracted from facial images are represented …