Jun Yan, Benyu Zhang, Ning Liu, Shuicheng Yan, Qiansheng Cheng, Weiguo Fan, ...
Abstract—Dimensionality reduction is an essential data preprocessing technique for large-scale and streaming data classification tasks. It can be used to improve both the efficiency and the...
Jun Yan, Benyu Zhang, Ning Liu, Shuicheng Yan, Qiansheng Cheng, Weiguo Fan, ...
Abstract—Dimensionality reduction is an essential data preprocessing technique for large-scale and streaming data classification tasks. It can be used to improve both the efficiency and the...
Ratio Rule Mining from Multiple Data Sources (2008)
Jun Yan, Ning Liu, Qiang Yang, Qiansheng Cheng
Abstract. Both multiple source data mining and streaming data mining problems have attracted much attention in the past decade. In contrast to traditional association-rule mining, to capture the...
Diverse Topic Phrase Extraction from Text Collection (2008)
Jilin Chen, Benyu Zhang, Dou Shen, Qiang Yang, Zheng Chen, Qiansheng Cheng
Keyword extraction is an efficient approach to managing an explosion of online text on the Web. Traditionally, an abstraction of the online text is constructed though keywords, which are extracted...
A Scalable Supervised Algorithm for Dimensionality Reduction on Streaming Data * (2008)
Jun Yan, Benyu Zhang, Shuicheng Yan, Ning Liu, Qiang Yang, Qiansheng Cheng, ...
Algorithms on streaming data have attracted increasing attention in the past decade. Among them, dimensionality reduction algorithms are greatly interesting due to the desirability of real tasks....
Jun Yan, Xiaobo Zhou, Qiong Yang, Ning Liu, Qiansheng Cheng
The lacking of automatic screen systems that can deal with large volume of time-lapse optical microscopy imaging is a bottleneck of modern bio-imaging research. In this paper, we propose an effective...
Jinwen Ma, Bin Gao, Yang Wang, Qiansheng Cheng
Under the Bayesian Ying–Yang (BYY) harmony learning theory, a harmony function has been developed on a BI-directional architecture of the BYY system for Gaussian mixture with an important feature...
An incremental subspace learning algorithm to categorize large scale text data (2005)
Jun Yan, Qiansheng Cheng, Qiang Yang, Benyu Zhang
Abstract. The dramatic growth in the number and size of on-line information sources has fueled increasing research interest in the incremental subspace learning problem. In this paper, we propose an...
Ocfs: Optimal orthogonal centroid feature selection for text categorization (2005)
Jun Yan, Ning Liu, Benyu Zhang, Shuicheng Yan, Zheng Chen, Qiansheng Cheng, ...
ABSTRACT 1 Text categorization is an important research area in many Information Retrieval (IR) applications. To save the storage space and computation time in text categorization, efficient and...
IMMC: Incremental Maximum Margin Criterion (2004)
Jun Yan, Jun Yan Benyu, Shuicheng Yan, Qiang Yang, Hua Li, Zheng Chen, ...
Subspace learning approaches have attracted much attention in academia recently. However, the classical batch algorithms no longer satisfy the applications on streaming data or large-scale data. To...
Ranking Prior Likelihood Distributions for Bayesian Shape Localization Framework (2003)
Shuicheng Yan, Mingjing Li, Hongjiang Zhang, Qiansheng Cheng
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood of local features...
Direct appearance models (2001)
Xinwen Hou, Stan Z. Li, Hongjiang Zhang, Qiansheng Cheng
Active appearance model (AAM), which makes ingenious use of both shape and texture constraints, is a powerful tool for face modeling, alignment and facial feature extraction under shape deformations...
Learning Spatially Localized, Parts-Based Representation (2001)
Stan Z. Li, Xinwen Hou, Hongjiang Zhang, Qiansheng Cheng
In this paper, we propose a novel method, called local nonnegative matrix factorization (LNMF), for learning spatially localized, parts-based subspace representation of visual patterns. An objective...