Birds may need to be identified for purposes such as environmental monitoring, follow-up,
and species detection in the ecological area. Automatic sound classifiers have been used to …

In multi-label classification tasks, each problem instance is associated with multiple classes
simultaneously. In such settings, the correlation between labels contain valuable information …

Effective features derived from an original hyperspectral image (HSI) are quite important to
improve the classification performance. An improved feature set, namely HGFM, is …

In the field of machine learning, collected data always have additional features which are
always referred as privileged information. Privileged information learning is mainly used to …

结构化支持向量机(Structural Support Vector Machine, SSVM) 是支持向量机(Support Vector
Machine, SVM) 的变体算法, 被广泛应用于多个领域. 阐述了SSVM 的发展过程 …

Multi-label learning is a meaningful supervised learning task in which each sample may
belong to multiple labels simultaneously. Due to this characteristic, multi-label learning is …

Twin support vector machine (TWSVM) is a new machine learning method, as opposed to
solving a single quadratic programming problem in support vector machine (SVM), which …

Based on the recently proposed projection twin support vector machine (PTSVM) and least
squares projection twin support vector machine (LSPTSVM), in this paper, we propose a …

The digital technologies that run based on users' content provide a platform for users to help
air their opinions on various aspects of a particular subject or product. The recommendation …

In the era of the big data, the accurate prediction of real-time traffic flow is essential to
making rational decisions on travel time, cost and route. To forecast traffic flow accurately …