Outlier detection has recently become an important problem in many industrial and financial applications. In this paper, a novel feature bagging approach for detecting outliers in...
Clustering is an essential data mining task with numerous applications. However, data in most real-life applications are high-dimensional in nature, and the related information of...
We propose an online topic model for sequentially analyzing the time evolution of topics in document collections. Topics naturally evolve with multiple timescales. For example, so...
One of the important approaches for Knowledge discovery and Data mining is to estimate unobserved variables because latent variables can indicate hidden and specific properties o...
Many real-world data mining tasks require the achievement of two distinct goals when applied to unseen data: first, to induce an accurate preference ranking, and second to give g...