Dimension reduction is a critical data preprocessing step for many database and data mining applications, such as efficient storage and retrieval of high-dimensional data. In the ...
Jieping Ye, Qi Li, Hui Xiong, Haesun Park, Ravi Ja...
Recent years have witnessed a dramatic increase in the quantity of image data collected, due to advances in fields such as medical imaging, reconnaissance, surveillance, astronomy...
This paper proposes a novel Data Envelopment Analysis (DEA) based approach for model combination. We first prove that for the 2-class classification problems DEA models identify t...
Analyzing data to find trends, correlations, and stable patterns is an important task in many industrial applications. This paper proposes a new technique based on parallel coordi...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Andreas Sc...
This paper proposes a data mining approach to modeling relationships among categories in image collection. In our approach, with image feature grouping, a visual dictionary is cre...
Subspace learning approaches have attracted much attention in academia recently. However, the classical batch algorithms no longer satisfy the applications on streaming data or la...
Jun Yan, Benyu Zhang, Shuicheng Yan, Qiang Yang, H...
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Given a user-specified minimum correlation threshold and a market basket database with N items and T transactions, an all-strong-pairs correlation query finds all item pairs with...