Xing Yong

Southwest University of Science and Technology

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i-10 index

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Anise M. S. Wu

University of Macau

Xinyue Liu

Dalian University of Technology

Tan Ben-yan

Hubei University

Quanzeng You

Microsoft Research (United Kingdom)

Hongfei Lin

Dalian University of Technology

Youping Chen

Huazhong University of Science and Technology

Chun Feng

Southwest University of Science and Technology

Rui Zhai

Southwest University of Science and Technology

Linlin Zong

Dalian University of Technology

Xiangyang Zhang

Institute of Psychology, Chinese Academy of Sciences

Cooperative Institutions

Dalian University of Technology

Southwest University of Science and Technology

Huazhong University of Science and Technology

Dalian University

Tianjin University of Technology

University of Macau

Stanford University

Nottingham Trent University

University of Illinois System

Hong Kong Shue Yan University

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An improved spectral clustering algorithm based on local neighbors in kernel space

Computer Science and Information Systems (2011)

Xinyue Liu Xing Yong Hongfei Lin

Similarity matrix is critical to the performance of spectral clustering. Mercer kernels have become popular largely due to its successes in applying kernel methods such as kernel PCA. A novel spectral clustering method is proposed based on local neighborhood in kernel space (SC-LNK), which assumes that each data point can be linearly reconstructed from its neighbors. The SC-LNK algorithm tries to project the data to a feature space by the Mercer kernel, and then learn a sparse matrix using linear reconstruction as the similarity graph for spectral clustering. Experiments have been performed on synthetic and real world data sets and have shown that spectral clustering based on linear reconstruction in kernel space outperforms the conventional spectral clustering and the other two algorithms, especially in real world data sets.

Spectral Clustering

Kernel (algebra)

Similarity (geometry)

10.2298/csis110415064l

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A Clustering Algorithm Based on Markov Chain Models

Journal of Computer Research and Development (2003)

Xing Yong

Clustering a set of univariate time series based on their dynamics is a popular problem that can be widely found in many research areas Because the common clustering algorithm can't directly be used to resolve this problem, a new approach to grouping time series is proposed This approach firstly models each time series as a Markov chain that captures the dynamic character of the time series, and then gets the clustering result to these time series by clustering the Markov chains Using this method, two different data sets are clustered, in which, one is real data, and the other is artificial data By qualitative and quantitative analysis, it is proved that both of the clustering results are good

Single-linkage clustering

Data stream clustering

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Application of life history theory to explain the association between childhood maltreatment and adulthood sleep problems in Chinese men with drug abuse: multiple mediating roles of emotion regulation, future-oriented coping, and anxiety

European journal of psychotraumatology (2024)

Chun Feng Anise M. S. Wu Youping Chen Xing Yong Rui Zhai

Despite the practical importance of addressing the drug user's sleep problems to enhance the efficacy of treatment and rehabilitation, little is known about whether and how history of childhood maltreatment relates to this issue. This study takes an evolutionary perspective to investigate the associations between history of childhood maltreatment and sleep problems in adults with drug abuse via their emotion regulation difficulties, future-oriented coping, and anxiety.

Association (psychology)

10.1080/20008066.2024.2411881

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Learning the BN Structure Based on the Sum of Mutual Information

Journal of Chongqing University. English Edition (2001)

Xing Yong

The Crossing Entropy is defined to scale the similar level of two probability distribution. In many papers on learning BN structure,the Crossing Entropy was used as an indicator of measuring the learning accuracy of an algorithm.The known scoring metrics for learning BN structure is analyzed in this paper,then a new scoring metrics Sum of Mutual Information is proposed based on the information theory.At last,two algorithm for learning BN structure by SIM is represented.

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Sampling for Nyström Extension-Based Spectral Clustering

ACM Transactions on Knowledge Discovery from Data (2016)

Xianchao Zhang Linlin Zong Quanzeng You Xing Yong

Sampling is the key aspect for Nyström extension based spectral clustering. Traditional sampling schemes select the set of landmark points on a whole and focus on how to lower the matrix approximation error. However, the matrix approximation error does not have direct impact on the clustering performance. In this article, we propose a sampling framework from an incremental perspective, i.e., the landmark points are selected one by one, and each next point to be sampled is determined by previously selected landmark points. Incremental sampling builds explicit relationships among landmark points; thus, they work together well and provide a theoretical guarantee on the clustering performance. We provide two novel analysis methods and propose two schemes for selecting-the-next-one of the framework. The first scheme is based on clusterability analysis, which provides a better guarantee on clustering performance than schemes based on matrix approximation error analysis. The second scheme is based on loss analysis, which provides maximized predictive ability of the landmark points on the (implicit) labels of the unsampled points. Experimental results on a wide range of benchmark datasets demonstrate the superiorities of our proposed incremental sampling schemes over existing sampling schemes.

Landmark

Spectral Clustering

Benchmark (surveying)

Hierarchical clustering

10.1145/2934693

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Citations (13)

Survey on Probability Models of Information Retrieval

Computer Science (2003)

Xing Yong

The study of mathematical models on information retrieval is an important area in the Information Retrieval community. Because of the uncertainty characteristic of IR, the probability model based on statistical probability is a promising model from recent to future. Those models can be classified into classical models and probability network models. Several famous models are introduced and their shortcomings are pointed out in this paper. We also clarify the relationship of these models and introduce a new models based on statistical language model curtly.

Divergence-from-randomness model

Probability model

Applied probability

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Testing for the applicability of company's balance-sheet model for financial crisis to China:An analysis based on dynamic panel data model

Xing Yong Tan Ben-yan

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STRESS FIELD OF DROPPED PLY REGION IN LAMINATES

Journal of Inner Mongolia Polytechnic University (1999)

Xing Yong

In this paper,the stress field of dropped ply region is studied using the moire interferometry method.Fringe patterns of the dropped region,which are collected respectively in the tensile and the pressing circumstances,are analyzed.Conclusion is drawn that the dropped ply region is destroyed by shear stress when it is in the tensile circumstance,while its failure in the pressing circumstance should be explained by the crack mechanism.The experimental results well coincide with the analytical results.

Stress field

Moiré pattern

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Viewing the Impact of Law of Property on Banking Industry from Grass-roots

Xing Yong

The implementation of the Law of Property will have many positive influences on the banking industry in China,the biggest of which is innovating the institution of real right for security,extending the space of real right for security,classifying registry system,adding public illustration modes,alternating value-orientation.This will not only help improve the security capability and financing ability of the enterprises,but further normalize the financing mode,providing the banking industry a more favorable legal guarantee.The Law of Property brings the banking industry opportunities,meanwhile,risk hidden trouble as well,making banking operation face bigger challenges,such as demurral registry,premonition registry,moveable mortgage and pledge,receivable pledge loans,and shortened maturity of real right for security,etc.These will make a higher requirement for banking operation and management.

Pledge

Accounts receivable

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Is "Luoying" The Weeping Flower

Journal of Heze Teachers College (2002)

Xing Yong

There have been many explanations of the character luo of luoying in Lisao . Some say it means begin, the other refer it to fall. Now a new meaning, droop , is put forward, with which the writ er of this paper doesn't agree. The paper demonstrates that luo ought to be explained as wither mainly from the point of literature.

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Punctuation

Original meaning

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