A new method for measuring uncertainty and fuzziness in rough set theory. - Jiye Liang; Kwai-Sang Chin; Chuangyin Dang; Richard C. M. Yam (Int. J. Gen. Syst., 2002)

The Algorithm on Knowledge Reduction in Incomplete Information Systems. - Jiye Liang; Zongben Xu (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2002)

Inclusion degree: a perspective on measures for rough set data analysis. - Zongben Xu; Jiye Liang; Chuangyin Dang; Kwai-Sang Chin (Inf. Sci., 2002)

Rough Set Data Analysis Algorithms for Incomplete Information Systems. - K. S. Chin; Jiye Liang; Chuangyin Dang (RSFDGrC, 2003)

The Information Entropy, Rough Entropy And Knowledge Granulation In Rough Set Theory. - Jiye Liang; Zhongzhi Shi (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2004)

Rough Set Approximation Based on Dynamic Granulation. - Jiye Liang; Yuhua Qian; Chengyuan Chu; Deyu Li; Junhong Wang (RSFDGrC (1), 2005)

Axiomatic Approach of Knowledge Granulation in Information System. - Jiye Liang; Yuhua Qian (Australian Conference on Artificial Intelligence, 2006)

A Measure Method for Indiscernibility in Imperfect Information System. - Jiye Liang; Jifang Pang (JCIS, 2006)

Combination Entropy and Combination Granulation in Incomplete Information System. - Yuhua Qian; Jiye Liang (RSKT, 2006)

Information entropy, rough entropy and knowledge granulation in incomplete information systems. - Jiye Liang; Z. Shi; Deyu Li; Mark J. Wierman (Int. J. Gen. Syst., 2006)

MGRS in Incomplete Information Systems. - Yuhua Qian; Jiye Liang; Chuangyin Dang (GrC, 2007)

Evaluation Method for Decision Rule Sets. - Yuhua Qian; Jiye Liang (RSFDGrC, 2007)

Study of decision implications based on formal concept analysis. - Kaishe Qu; Yanhui Zhai; Jiye Liang; Min Chen (Int. J. Gen. Syst., 2007)

Granulation Operators on a Knowledge Base. - Yuhua Qian; Jiye Liang; Wei Wei 018 (GrC, 2008)

Change Mechanism of a Decision Table's Decision Performance caused by Attribute Reductions. - Wei Wei 018; Jiye Liang; Yuhua Qian (GrC, 2008)

Consistency and Fuzziness in Ordered Decision Tables. - Yuhua Qian; Jiye Liang; Wei Wei 018; Feng Wang 038 (RSKT, 2008)

Information granules and entropy theory in information systems. - Jiye Liang; Yuhua Qian (Sci. China Ser. F Inf. Sci., 2008)

Converse approximation and rule extraction from decision tables in rough set theory. - Yuhua Qian; Jiye Liang; Chuangyin Dang (Comput. Math. Appl., 2008)

Interval ordered information systems. - Yuhua Qian; Jiye Liang; Chuangyin Dang (Comput. Math. Appl., 2008)

On the evaluation of the decision performance of an incomplete decision table. - Yuhua Qian; Chuangyin Dang; Jiye Liang; Haiyun Zhang; Jianmin Ma (Data Knowl. Eng., 2008)

Consistency measure, inclusion degree and fuzzy measure in decision tables. - Yuhua Qian; Jiye Liang; Chuangyin Dang (Fuzzy Sets Syst., 2008)

Combination Entropy and Combination Granulation in Rough Set Theory. - Yuhua Qian; Jiye Liang (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2008)

Uncertainty Measure of Rough Sets Based on a Knowledge Granulation for Incomplete Information Systems. - Junhong Wang; Jiye Liang; Yuhua Qian; Chuangyin Dang (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2008)

Measures for evaluating the decision performance of a decision table in rough set theory. - Yuhua Qian; Jiye Liang; Deyu Li; Haiyun Zhang; Chuangyin Dang (Inf. Sci., 2008)

Research on Rough Set Theory and Applications in China. - Guoyin Wang 001; Qinghua Zhang 001; Houkuan Huang; Dongyi Ye; Qinghua Hu; Xuegang Hu; Zhongzhi Shi; Yongli Li; Lin Shang 001; Liping An; Ying Sai; Shanben Chen; et al. (Trans. Rough Sets, 2008)

An attribute reduction approach and its accelerated version for hybrid data. - Wei Wei 018; Jiye Liang; Yuhua Qian; Feng Wang 038 (IEEE ICCI, 2009)

A Time-Reduction Strategy to Feature Selection in Rough Set Theory. - Hongxing Chen; Yuhua Qian; Jiye Liang; Wei Wei 018; Feng Wang 038 (RSKT, 2009)

Apply Inversion Order Number Genetic Algorithm to the Job Shop Scheduling Problem. - Xiaomei Yang; Jianchao Zeng 001; Jiye Liang (WGEC, 2009)

An initialization method for the K-Means algorithm using neighborhood model. - Fuyuan Cao; Jiye Liang; Guang Jiang (Comput. Math. Appl., 2009)

A new initialization method for categorical data clustering. - Fuyuan Cao; Jiye Liang; Liang Bai (Expert Syst. Appl., 2009)

Knowledge structure, knowledge granulation and knowledge distance in a knowledge base. - Yuhua Qian; Jiye Liang; Chuangyin Dang (Int. J. Approx. Reason., 2009)

A New Method for Measuring the Uncertainty in Incomplete Information Systems. - Yuhua Qian; Jiye Liang; Feng Wang 038 (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2009)

A new measure of uncertainty based on knowledge granulation for rough sets. - Jiye Liang; Junhong Wang; Yuhua Qian (Inf. Sci., 2009)

Set-valued ordered information systems. - Yuhua Qian; Chuangyin Dang; Jiye Liang; Dawei Tang (Inf. Sci., 2009)

A deterministic annealing algorithm for approximating a solution of the min-bisection problem. - Chuangyin Dang; Wei Ma; Jiye Liang (Neural Networks, 2009)

On Partial Order Relations in Granular Computing. - Hongxing Chen; Yuhua Qian; Jiye Liang; Wei Wei 018 (GrC, 2010)

A heuristic method to attribute reduction for concept lattice. - Junhong Wang; Jiye Liang; Yuhua Qian (ICMLC, 2010)

Positive approximation: An accelerator for attribute reduction in rough set theory. - Yuhua Qian; Jiye Liang; Witold Pedrycz; Chuangyin Dang (Artif. Intell., 2010)

Comparative study of decision performance of decision tables induced by attribute reductions. - Wei Wei 018; Jiye Liang; Yuhua Qian; Feng Wang 038; Chuangyin Dang (Int. J. Gen. Syst., 2010)

MGRS: A multi-granulation rough set. - Yuhua Qian; Jiye Liang; Yiyu Yao; Chuangyin Dang (Inf. Sci., 2010)

Approximation reduction in inconsistent incomplete decision tables. - Yuhua Qian; Jiye Liang; Deyu Li; Feng Wang 038; Nannan Ma (Knowl. Based Syst., 2010)

A Framework for Clustering Categorical Time-Evolving Data. - Fuyuan Cao; Jiye Liang; Liang Bai; Xingwang Zhao; Chuangyin Dang (IEEE Trans. Fuzzy Syst., 2010)

Incomplete Multigranulation Rough Set. - Yuhua Qian; Jiye Liang; Chuangyin Dang (IEEE Trans. Syst. Man Cybern. Part A, 2010)

Closed-Label Concept Lattice Based Rule Extraction Approach. - Junhong Wang; Jiye Liang; Yuhua Qian (ICIC (3), 2011)

Uncertainty and Feature Selection in Rough Set Theory. - Jiye Liang (RSKT, 2011)

An Efficient Fuzzy-Rough Attribute Reduction Approach. - Yuhua Qian; Chao Li; Jiye Liang (RSKT, 2011)

How to organize data with measurement errors? - Yuhua Qian; Jiye Liang (SMC, 2011)

A data labeling method for clustering categorical data. - Fuyuan Cao; Jiye Liang (Expert Syst. Appl., 2011)

An initialization method to simultaneously find initial cluster centers and the number of clusters for clustering categorical data. - Liang Bai; Jiye Liang; Chuangyin Dang (Knowl. Based Syst., 2011)

A novel attribute weighting algorithm for clustering high-dimensional categorical data. - Liang Bai; Jiye Liang; Chuangyin Dang; Fuyuan Cao (Pattern Recognit., 2011)

An efficient accelerator for attribute reduction from incomplete data in rough set framework. - Yuhua Qian; Jiye Liang; Witold Pedrycz; Chuangyin Dang (Pattern Recognit., 2011)

The dynamical neighborhood selection based on the sampling density and manifold curvature for isometric data embedding. - Xiaofang Gao; Jiye Liang (Pattern Recognit. Lett., 2011)

Information Granularity in Fuzzy Binary GrC Model. - Yuhua Qian; Jiye Liang; Wei-zhi Z. Wu; Chuangyin Dang (IEEE Trans. Fuzzy Syst., 2011)

Feature selection for large-scale data sets in GrC. - Jiye Liang (GrC, 2012)

Variable precision multi-granulation rough set. - Wei Wei 018; Jiye Liang; Yuhua Qian; Feng Wang 038 (GrC, 2012)

Fuzziness-Preserving Attribute Reduction from Hybrid Data. - Wei Wei 018; Jiye Liang; Yuhua Qian; Junhong Wang (IScIDE, 2012)

Information Granularity and Granular Structure in Decision Making. - Baoli Wang; Jiye Liang; Yuhua Qian (RSKT, 2012)

Partial ordering of information granulations: a further investigation. - Yuhua Qian; Chuangyin Dang; Jiye Liang; Wei-Zhi Wu 001 (Expert Syst. J. Knowl. Eng., 2012)

A cluster centers initialization method for clustering categorical data. - Liang Bai; Jiye Liang; Chuangyin Dang; Fuyuan Cao (Expert Syst. Appl., 2012)

An efficient rough feature selection algorithm with a multi-granulation view. - Jiye Liang; Feng Wang 038; Chuangyin Dang; Yuhua Qian (Int. J. Approx. Reason., 2012)

A comparative study of rough sets for hybrid data. - Wei Wei 018; Jiye Liang; Yuhua Qian (Inf. Sci., 2012)

A dissimilarity measure for the k-Modes clustering algorithm. - Fuyuan Cao; Jiye Liang; Deyu Li; Liang Bai; Chuangyin Dang (Knowl. Based Syst., 2012)

Distance: A more comprehensible perspective for measures in rough set theory. - Jiye Liang; Ru Li 001; Yuhua Qian (Knowl. Based Syst., 2012)

Evaluation of the decision performance of the decision rule set from an ordered decision table. - Yuhua Qian; Jiye Liang; Peng Song 004; Chuangyin Dang; Wei Wei 018 (Knowl. Based Syst., 2012)

A two-grade approach to ranking interval data. - Peng Song 004; Jiye Liang; Yuhua Qian (Knowl. Based Syst., 2012)

Determining the number of clusters using information entropy for mixed data. - Jiye Liang; Xingwang Zhao; Deyu Li; Fuyuan Cao; Chuangyin Dang (Pattern Recognit., 2012)

The K -Means-Type Algorithms Versus Imbalanced Data Distributions. - Jiye Liang; Liang Bai; Chuangyin Dang; Fuyuan Cao (IEEE Trans. Fuzzy Syst., 2012)

Contact Network Model with Covert Infection. - Xiaomei Yang; Jianchao Zeng 001; Jiye Liang (ICSI (2), 2013)

Attribute reduction for dynamic data sets. - Feng Wang 038; Jiye Liang; Chuangyin Dang (Appl. Soft Comput., 2013)

A novel fuzzy clustering algorithm with between-cluster information for categorical data. - Liang Bai; Jiye Liang; Chuangyin Dang; Fuyuan Cao (Fuzzy Sets Syst., 2013)

Decision-relative discernibility matrices in the sense of entropies. - Wei Wei 018; Jiye Liang; Junhong Wang; Yuhua Qian (Int. J. Gen. Syst., 2013)

A weighting k-modes algorithm for subspace clustering of categorical data. - Fuyuan Cao; Jiye Liang; Deyu Li; Xingwang Zhao (Neurocomputing, 2013)

Fast global k-means clustering based on local geometrical information. - Liang Bai; Jiye Liang; Chao Sui; Chuangyin Dang (Inf. Sci., 2013)

Multigranulation rough sets: From partition to covering. - Guoping Lin; Jiye Liang; Yuhua Qian (Inf. Sci., 2013)

Can fuzzy entropies be effective measures for evaluating the roughness of a rough set? - Wei Wei 018; Jiye Liang; Yuhua Qian; Chuangyin Dang (Inf. Sci., 2013)

An accelerator for attribute reduction based on perspective of objects and attributes. - Jiye Liang; Junrong Mi; Wei Wei 018; Feng Wang 038 (Knowl. Based Syst., 2013)

Attribute reduction: A dimension incremental strategy. - Feng Wang 038; Jiye Liang; Yuhua Qian (Knowl. Based Syst., 2013)

Consistency-preserving attribute reduction in fuzzy rough set framework. - Yuhua Qian; Jiye Liang; Wei Wei 018 (Int. J. Mach. Learn. Cybern., 2013)

The Impact of Cluster Representatives on the Convergence of the (K)-Modes Type Clustering. - Liang Bai; Jiye Liang; Chuangyin Dang; Fuyuan Cao (IEEE Trans. Pattern Anal. Mach. Intell., 2013)

A Novel Intelligent Multi-attribute Three-Way Group Sorting Method Based on Dempster-Shafer Theory. - Baoli Wang; Jiye Liang (RSKT, 2014)

Preorder Information Based Attributes' Weights Learning in Multi-attribute Decision Making. - Baoli Wang; Jiye Liang; Yuhua Qian (Fundam. Informaticae, 2014)

Set-based granular computing: A lattice model. - Yuhua Qian; Hu Zhang 003; Feijiang Li; Qinghua Hu; Jiye Liang (Int. J. Approx. Reason., 2014)

Multigranulation decision-theoretic rough sets. - Yuhua Qian; Hu Zhang 003; Yanli Sang; Jiye Liang (Int. J. Approx. Reason., 2014)

The k-modes type clustering plus between-cluster information for categorical data. - Liang Bai; Jiye Liang (Neurocomputing, 2014)

Trend analysis of categorical data streams with a concept change method. - Fuyuan Cao; Joshua Zhexue Huang; Jiye Liang (Inf. Sci., 2014)

Pessimistic rough set based decisions: A multigranulation fusion strategy. - Yuhua Qian; Shunyong Li; Jiye Liang; Zhongzhi Shi; Feng Wang 038 (Inf. Sci., 2014)

Topological approach to multigranulation rough sets. - Guoping Lin; Jiye Liang; Yuhua Qian (Int. J. Mach. Learn. Cybern., 2014)

A rule-extraction framework under multigranulation rough sets. - Xin Liu; Yuhua Qian; Jiye Liang (Int. J. Mach. Learn. Cybern., 2014)

A simple and effective outlier detection algorithm for categorical data. - Xingwang Zhao; Jiye Liang; Fuyuan Cao (Int. J. Mach. Learn. Cybern., 2014)

A Group Incremental Approach to Feature Selection Applying Rough Set Technique. - Jiye Liang; Feng Wang 038; Chuangyin Dang; Yuhua Qian (IEEE Trans. Knowl. Data Eng., 2014)

Decision-Oriented Rough Set Methods. - Jiye Liang (RSFDGrC, 2015)

Methods and Practices of Three-Way Decisions for Complex Problem Solving. - Hong Yu 007; Guoyin Wang 001; Baoqing Hu; Xiuyi Jia; Huaxiong Li; Tianrui Li 001; Decui Liang; Jiye Liang; Baoxiang Liu; Dun Liu; Jianmin Ma; Duoqian Miao 001; et al. (RSKT, 2015)

Cluster validity functions for categorical data: a solution-space perspective. - Liang Bai; Jiye Liang (Data Min. Knowl. Discov., 2015)

Fuzzy-rough feature selection accelerator. - Yuhua Qian; Qi Wang; Honghong Cheng; Jiye Liang; Chuangyin Dang (Fuzzy Sets Syst., 2015)

Uncertainty Measures for Multigranulation Approximation Space. - Guoping Lin; Jiye Liang; Yuhua Qian (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2015)

A Normalized Numerical Scaling Method for the Unbalanced Multi-Granular Linguistic Sets. - Baoli Wang; Jiye Liang; Yuhua Qian; Chuangyin Dang (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2015)

An improved incremental nonlinear dimensionality reduction for isometric data embedding. - Xiaofang Gao; Jiye Liang (Inf. Process. Lett., 2015)

An information fusion approach by combining multigranulation rough sets and evidence theory. - Guoping Lin; Jiye Liang; Yuhua Qian (Inf. Sci., 2015)

Compacted decision tables based attribute reduction. - Wei Wei 018; Junhong Wang; Jiye Liang; Xin Mi; Chuangyin Dang (Knowl. Based Syst., 2015)

Determining decision makers' weights in group ranking: a granular computing method. - Baoli Wang; Jiye Liang; Yuhua Qian (Int. J. Mach. Learn. Cybern., 2015)

Fuzzy Granular Structure Distance. - Yuhua Qian; Yebin Li; Jiye Liang; Guoping Lin; Chuangyin Dang (IEEE Trans. Fuzzy Syst., 2015)

Fusing Monotonic Decision Trees. - Yuhua Qian; Hang Xu; Jiye Liang; Bing Liu 001; Jieting Wang (IEEE Trans. Knowl. Data Eng., 2015)

Adaptation Approaches in Unsupervised Learning: A Survey of the State-of-the-Art and Future Directions. - Junhong Wang; Yun-Qian Miao; Alaa M. Khamis; Fakhri Karray; Jiye Liang (ICIAR, 2016)

An efficient feature selection algorithm for hybrid data. - Feng Wang 038; Jiye Liang (Neurocomputing, 2016)

Fuzzy rough approximations for set-valued data. - Wei Wei 018; Junbiao Cui; Jiye Liang; Junhong Wang (Inf. Sci., 2016)

一种基于抽样的大规模混合数据聚类集成算法 (Clustering Ensemble Algorithm for Large-scale Mixed Data Based on Sampling). - Tianjie Pang; Jiye Liang (计算机科学, 2016)

A fuzzy multigranulation decision-theoretic approach to multi-source fuzzy information systems. - Guoping Lin; Jiye Liang; Yuhua Qian; Jinjin Li 001 (Knowl. Based Syst., 2016)

Comparison study of orthonormal representations of functional data in classification. - Yinfeng Meng; Jiye Liang; Yuhua Qian (Knowl. Based Syst., 2016)

Decision-theoretic rough sets under dynamic granulation. - Yanli Sang; Jiye Liang; Yuhua Qian (Knowl. Based Syst., 2016)

An Optimization Model for Clustering Categorical Data Streams with Drifting Concepts. - Liang Bai; Xueqi Cheng; Jiye Liang; Huawei Shen (IEEE Trans. Knowl. Data Eng., 2016)

An Approach to Cold-Start Link Prediction: Establishing Connections between Non-Topological and Topological Information. - Zhiqiang Wang 005; Jiye Liang; Ru Li 001; Yuhua Qian (IEEE Trans. Knowl. Data Eng., 2016)

Space Structure and Clustering of Categorical Data. - Yuhua Qian; Feijiang Li; Jiye Liang; Bing Liu 001; Chuangyin Dang (IEEE Trans. Neural Networks Learn. Syst., 2016)

Local Bayes Risk Minimization Based Stopping Strategy for Hierarchical Classification. - Yu Wang 106; Qinghua Hu; Yucan Zhou; Hong Zhao 002; Yuhua Qian; Jiye Liang (ICDM, 2017)

A fuzzy SV-k-modes algorithm for clustering categorical data with set-valued attributes. - Fuyuan Cao; Joshua Zhexue Huang; Jiye Liang (Appl. Math. Comput., 2017)

k-mw-modes: An algorithm for clustering categorical matrix-object data. - Fuyuan Cao; Liqin Yu; Joshua Zhexue Huang; Jiye Liang (Appl. Soft Comput., 2017)

An adaptive consensus method for multi-attribute group decision making under uncertain linguistic environment. - Jifang Pang; Jiye Liang; Peng Song 004 (Appl. Soft Comput., 2017)

Local multigranulation decision-theoretic rough sets. - Yuhua Qian; Xinyan Liang; Guoping Lin; Qian Guo; Jiye Liang (Int. J. Approx. Reason., 2017)

An efficient instance selection algorithm for k nearest neighbor regression. - Yunsheng Song; Jiye Liang; Jing Lu; Xingwang Zhao (Neurocomputing, 2017)

Fast graph clustering with a new description model for community detection. - Liang Bai; Xueqi Cheng; Jiye Liang; Yike Guo (Inf. Sci., 2017)

Multigranulation information fusion: A Dempster-Shafer evidence theory-based clustering ensemble method. - Feijiang Li; Yuhua Qian; Jieting Wang; Jiye Liang (Inf. Sci., 2017)

Grouping granular structures in human granulation intelligence. - Yuhua Qian; Honghong Cheng; Jieting Wang; Jiye Liang; Witold Pedrycz; Chuangyin Dang (Inf. Sci., 2017)

A multi-view OVA model based on decision tree for multi-classification tasks. - Xiaoqiang Guan; Jiye Liang; Yuhua Qian; Jifang Pang (Knowl. Based Syst., 2017)

Fast density clustering strategies based on the k-means algorithm. - Liang Bai; Xueqi Cheng; Jiye Liang; Huawei Shen; Yike Guo (Pattern Recognit., 2017)

Clustering ensemble selection for categorical data based on internal validity indices. - Xingwang Zhao; Jiye Liang; Chuangyin Dang (Pattern Recognit., 2017)

A sequential ensemble clusterings generation algorithm for mixed data. - Xingwang Zhao; Fuyuan Cao; Jiye Liang (Appl. Math. Comput., 2018)

A cautious ranking methodology with its application for stock screening. - Peng Song 004; Jiye Liang; Yuhua Qian; Wei Wei 018; Feng Wang 038 (Appl. Soft Comput., 2018)

Exploiting user-to-user topic inclusion degree for link prediction in social-information networks. - Zhiqiang Wang 005; Jiye Liang; Ru Li 001 (Expert Syst. Appl., 2018)

Local rough set: A solution to rough data analysis in big data. - Yuhua Qian; Xinyan Liang; Qi Wang; Jiye Liang; Bing Liu 001; Andrzej Skowron; Yiyu Yao; Jianmin Ma; Chuangyin Dang (Int. J. Approx. Reason., 2018)

A new distance with derivative information for functional k-means clustering algorithm. - Yinfeng Meng; Jiye Liang; Fuyuan Cao; Yijun He (Inf. Sci., 2018)

一种基于空间变换的协同过滤推荐算法 (Collaborative Filtering Recommendation Algorithm Based on Space Transformation). - Xingwang Zhao; Jiye Liang; Lanjie Guo (计算机科学, 2018)

A novel community detection algorithm based on simplification of complex networks. - Liang Bai; Jiye Liang; Hangyuan Du; Yike Guo (Knowl. Based Syst., 2018)

A fusion probability matrix factorization framework for link prediction. - Zhiqiang Wang 005; Jiye Liang; Ru Li 001 (Knowl. Based Syst., 2018)

Local neighborhood rough set. - Qi Wang; Yuhua Qian; Xinyan Liang; Qian Guo; Jiye Liang (Knowl. Based Syst., 2018)

Discernibility matrix based incremental attribute reduction for dynamic data. - Wei Wei 018; Xiaoying Wu; Jiye Liang; Junbiao Cui; Yijun Sun (Knowl. Based Syst., 2018)

Hesitant fuzzy linguistic rough set over two universes model and its applications. - Chao Zhang 046; Deyu Li; Jiye Liang (Int. J. Mach. Learn. Cybern., 2018)

An Ensemble Clusterer of Multiple Fuzzy k-Means Clusterings to Recognize Arbitrarily Shaped Clusters. - Liang Bai; Jiye Liang; Yike Guo (IEEE Trans. Fuzzy Syst., 2018)

An Algorithm for Clustering Categorical Data With Set-Valued Features. - Fuyuan Cao; Joshua Zhexue Huang; Jiye Liang; Xingwang Zhao; Yinfeng Meng; Kai Feng; Yuhua Qian (IEEE Trans. Neural Networks Learn. Syst., 2018)

Sign fusion of multiple QPNs based on qualitative mutual information. - Yali Lv; Jiye Liang; Yuhua Qian; Jiajie Wu; Suqin Ji (Int. J. Comput. Sci. Eng., 2019)

Deviation Degree: A Perspective on Score Functions in Hesitant Fuzzy Sets. - Baoli Wang; Jiye Liang; Jifang Pang (Int. J. Fuzzy Syst., 2019)

Hierarchical division clustering framework for categorical data. - Wei Wei 018; Jiye Liang; Xinyao Guo; Peng Song 004; Yijun Sun (Neurocomputing, 2019)

Information fusion in rough set theory : An overview. - Wei Wei 018; Jiye Liang (Inf. Fusion, 2019)

Protein complex detection algorithm based on multiple topological characteristics in PPI networks. - Jie Wang 046; Jiye Liang; Wenping Zheng; Xingwang Zhao; Junfang Mu (Inf. Sci., 2019)

基于类别随机化的随机森林算法 (Randomization of Classes Based Random Forest Algorithm). - Xiaoqiang Guan; Jifang Pang; Jiye Liang (计算机科学, 2019)

一种基于同配性的重叠蛋白质复合体检测算法 (Overlapping Protein Complexes Detection Algorithm Based on Assortativity in PPI Networks). - Jie Wang 046; Jiye Liang; Xingwang Zhao; Wenping Zheng (计算机科学, 2019)

A novel edge rewiring strategy for tuning structural properties in networks. - Junfang Mu; Wenping Zheng; Jie Wang 046; Jiye Liang (Knowl. Based Syst., 2019)

A stratified sampling based clustering algorithm for large-scale data. - Xingwang Zhao; Jiye Liang; Chuangyin Dang (Knowl. Based Syst., 2019)

Local dense mixed region cutting + global rebalancing: a method for imbalanced text sentiment classification. - Yang Li 074; Jie Wang 046; Suge Wang; Jiye Liang; Juanzi Li (Int. J. Mach. Learn. Cybern., 2019)

An accelerator for support vector machines based on the local geometrical information and data partition. - Yunsheng Song; Jiye Liang; Feng Wang 038 (Int. J. Mach. Learn. Cybern., 2019)

Accelerating incremental attribute reduction algorithm by compacting a decision table. - Wei Wei 018; Peng Song 004; Jiye Liang; Xiaoying Wu (Int. J. Mach. Learn. Cybern., 2019)

An Ensemble Classification Algorithm Based on Information Entropy for Data Streams. - Junhong Wang; Shuliang Xu; Bingqian Duan; Caifeng Liu; Jiye Liang (Neural Process. Lett., 2019)

Cooperative Hybrid Semi-Supervised Learning for Text Sentiment Classification. - Yang Li 074; Ying Lv; Suge Wang; Jiye Liang; Juanzi Li; Xiaoli Li 001 (Symmetry, 2019)

Intuitionistic Fuzzy Rough Set-Based Granular Structures and Attribute Subset Selection. - Anhui Tan; Wei-Zhi Wu 001; Yuhua Qian; Jiye Liang; Jinkun Chen; Jinjin Li 001 (IEEE Trans. Fuzzy Syst., 2019)

An Information-Theoretical Framework for Cluster Ensemble. - Liang Bai; Jiye Liang; Hangyuan Du; Yike Guo (IEEE Trans. Knowl. Data Eng., 2019)

A Three-Level Optimization Model for Nonlinearly Separable Clustering. - Liang Bai; Jiye Liang (AAAI, 2020)

A Cluster-Weighted Kernel K-Means Method for Multi-View Clustering. - Jing Liu; Fuyuan Cao; Xiao-Zhi Gao 001; Liqin Yu; Jiye Liang (AAAI, 2020)

Sparse Subspace Clustering with Entropy-Norm. - Liang Bai; Jiye Liang (ICML, 2020)

Combining attribute content and label information for categorical data ensemble clustering. - Liqin Yu; Fuyuan Cao; Xingwang Zhao; Xiaodan Yang; Jiye Liang (Appl. Math. Comput., 2020)

An accelerator for the logistic regression algorithm based on sampling on-demand. - Jiye Liang; Yunsheng Song; Deyu Li; Zhiqiang Wang 005; Chuangyin Dang (Sci. China Inf. Sci., 2020)

A naive learning algorithm for class-bridge-decomposable multidimensional Bayesian network classifiers. - Yali Lv; Weixin Hu; Jiye Liang; Yuhua Qian; Junzhong Miao (Concurr. Comput. Pract. Exp., 2020)

Multi-attribute group decision-making method based on multi-granulation weights and three-way decisions. - Jifang Pang; Xiaoqiang Guan; Jiye Liang; Baoli Wang; Peng Song 004 (Int. J. Approx. Reason., 2020)

A Novel Preference Measure for Multi-Granularity Probabilistic Linguistic Term Sets and its Applications in Large-Scale Group Decision-Making. - Baoli Wang; Jiye Liang (Int. J. Fuzzy Syst., 2020)

A multiple k-means clustering ensemble algorithm to find nonlinearly separable clusters. - Liang Bai; Jiye Liang; Fuyuan Cao (Inf. Fusion, 2020)

A fusion collaborative filtering method for sparse data in recommender systems. - Chenjiao Feng; Jiye Liang; Peng Song 004; Zhiqiang Wang 005 (Inf. Sci., 2020)

Multi-granularity three-way decisions with adjustable hesitant fuzzy linguistic multigranulation decision-theoretic rough sets over two universes. - Chao Zhang 046; Deyu Li; Jiye Liang (Inf. Sci., 2020)

Interval-valued hesitant fuzzy multi-granularity three-way decisions in consensus processes with applications to multi-attribute group decision making. - Chao Zhang 046; Deyu Li; Jiye Liang (Inf. Sci., 2020)

基于极端评分行为的相似度计算 (New Similarity Measure Based on Extremely Rating Behavior). - Chenjiao Feng; Jiye Liang; Peng Song 004; Zhiqiang Wang 005 (计算机科学, 2020)

Deconvolutional neural network for image super-resolution. - Feilong Cao; Kaixuan Yao; Jiye Liang (Neural Networks, 2020)

New label propagation algorithm with pairwise constraints. - Liang Bai; Junbin Wang; Jiye Liang; Hangyuan Du (Pattern Recognit., 2020)

Fusing Fuzzy Monotonic Decision Trees. - Jieting Wang; Yuhua Qian; Feijiang Li; Jiye Liang; Weiping Ding 001 (IEEE Trans. Fuzzy Syst., 2020)

An outlier detection algorithm for categorical matrix-object data. - Fuyuan Cao; Xiaolin Wu; Liqin Yu; Jiye Liang (Appl. Soft Comput., 2021)

BIC-based node order learning for improving Bayesian network structure learning. - Yali Lv; Junzhong Miao; Jiye Liang; Ling Chen; Yuhua Qian (Frontiers Comput. Sci., 2021)

Fuzzy rough discrimination and label weighting for multi-label feature selection. - Anhui Tan; Jiye Liang; Wei-Zhi Wu 001; Jia Zhang; Lin Sun 002; Chao Chen (Neurocomputing, 2021)

Semi-supervised learning with mixed-order graph convolutional networks. - Jie Wang 046; Jianqing Liang; Junbiao Cui; Jiye Liang (Inf. Sci., 2021)

k-Mnv-Rep: A k-type clustering algorithm for matrix-object data. - Liqin Yu; Fuyuan Cao; Xiao-Zhi Gao 001; Jing Liu; Jiye Liang (Inf. Sci., 2021)

A community detection algorithm based on graph compression for large-scale social networks. - Xingwang Zhao; Jiye Liang; Jie Wang 046 (Inf. Sci., 2021)

A Unified Sample Selection Framework for Output Noise Filtering: An Error-Bound Perspective. - Gaoxia Jiang; Wenjian Wang; Yuhua Qian; Jiye Liang (J. Mach. Learn. Res., 2021)

Graph-based semi-supervised learning via improving the quality of the graph dynamically. - Jiye Liang; Junbiao Cui; Jie Wang 046; Wei Wei 018 (Mach. Learn., 2021)

Metric learning with clustering-based constraints. - Xinyao Guo; Chuangyin Dang; Jianqing Liang; Wei Wei 018; Jiye Liang (Int. J. Mach. Learn. Cybern., 2021)

Logic could be learned from images. - Qian Guo; Yuhua Qian; Xinyan Liang; Yanhong She; Deyu Li; Jiye Liang (Int. J. Mach. Learn. Cybern., 2021)

MAGDM-oriented dual hesitant fuzzy multigranulation probabilistic models based on MULTIMOORA. - Chao Zhang 046; Deyu Li; Jiye Liang; Baoli Wang (Int. J. Mach. Learn. Cybern., 2021)

Semi-Supervised Clustering With Constraints of Different Types From Multiple Information Sources. - Liang Bai; Jiye Liang; Fuyuan Cao (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Deep neural network compression through interpretability-based filter pruning. - Kaixuan Yao; Feilong Cao; Yee Leung; Jiye Liang (Pattern Recognit., 2021)

Controlling Underestimation Bias in Reinforcement Learning via Quasi-median Operation. - Wei Wei 018; Yujia Zhang; Jiye Liang; Lin Li 090; Yuze Li (AAAI, 2022)

Instance Selection: A Bayesian Decision Theory Perspective. - Qingqiang Chen; Fuyuan Cao; Ying Xing; Jiye Liang (AAAI, 2022)

Efficient Causal Structure Learning from Multiple Interventional Datasets with Unknown Targets. - Yunxia Wang; Fuyuan Cao; Kui Yu; Jiye Liang (AAAI, 2022)

Dual Bidirectional Graph Convolutional Networks for Zero-shot Node Classification. - Qin Yue 002; Jiye Liang; Junbiao Cui; Liang Bai (KDD, 2022)

Fuzzy Learning Machine. - Junbiao Cui; Jiye Liang (NeurIPS, 2022)

Hypergraphs: Concepts, Applications and Analysis. - Wenping Zheng; Meilin Liu; Jiye Liang (PAAP, 2022)

Multi-Scale Variational Graph AutoEncoder for Link Prediction. - Zhihao Guo; Feng Wang 038; Kaixuan Yao; Jiye Liang; Zhiqiang Wang 005 (WSDM, 2022)

Multi-view graph convolutional networks with attention mechanism. - Kaixuan Yao; Jiye Liang; Jianqing Liang; Ming Li 065; Feilong Cao (Artif. Intell., 2022)

Incomplete multi-view clustering via local and global co-regularization. - Jiye Liang; Xiaolin Liu; Liang Bai; Fuyuan Cao; Dianhui Wang 001 (Sci. China Inf. Sci., 2022)

A Bayesian matrix factorization model for dynamic user embedding in recommender system. - Kaihan Zhang; Zhiqiang Wang 005; Jiye Liang; Xingwang Zhao (Frontiers Comput. Sci., 2022)

Centroids-guided deep multi-view K-means clustering. - Jing Liu; Fuyuan Cao; Jiye Liang (Inf. Sci., 2022)

Weak multi-label learning with missing labels via instance granular discrimination. - Anhui Tan; Xiaowan Ji; Jiye Liang; Yuzhi Tao; Wei-Zhi Wu 001; Witold Pedrycz (Inf. Sci., 2022)

An unsupervised multi-manifold discriminant isomap algorithm based on the pairwise constraints. - Xiaofang Gao; Jiye Liang; Wenjian Wang; Xuefei Bai; Lina Jia (Int. J. Mach. Learn. Cybern., 2022)

Hierarchical metric learning with intra-level and inter-level regularization. - Lin Li 090; Ting Li; Wei Wei 018; Xinyao Guo; Jiye Liang (Int. J. Mach. Learn. Cybern., 2022)

Clustering mixed type data: a space structure-based approach. - Feijiang Li; Yuhua Qian; Jieting Wang; Furong Peng; Jiye Liang (Int. J. Mach. Learn. Cybern., 2022)

Accelerating ReliefF using information granulation. - Wei Wei 018; Da Wang; Jiye Liang (Int. J. Mach. Learn. Cybern., 2022)

AF: An Association-Based Fusion Method for Multi-Modal Classification. - Xinyan Liang; Yuhua Qian; Qian Guo; Honghong Cheng; Jiye Liang (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

A categorical data clustering framework on graph representation. - Liang Bai; Jiye Liang (Pattern Recognit., 2022)

Self-supervised spectral clustering with exemplar constraints. - Liang Bai; Yunxiao Zhao; Jiye Liang (Pattern Recognit., 2022)

Metric learning via perturbing hard-to-classify instances. - Xinyao Guo; Wei Wei 018; Jianqing Liang; Chuangyin Dang; Jiye Liang (Pattern Recognit., 2022)

Semi-supervised partial multi-label classification via consistency learning. - Anhui Tan; Jiye Liang; Wei-Zhi Wu 001; Jia Zhang (Pattern Recognit., 2022)

Graph convolutional autoencoders with co-learning of graph structure and node attributes. - Jie Wang 046; Jiye Liang; Kaixuan Yao; Jianqing Liang; Dianhui Wang 001 (Pattern Recognit., 2022)

Cross-modal propagation network for generalized zero-shot learning. - Ting Guo; Jianqing Liang; Jiye Liang; Guo-Sen Xie (Pattern Recognit. Lett., 2022)

A group incremental approach for feature selection on hybrid data. - Feng Wang 038; Wei Wei 018; Jiye Liang (Soft Comput., 2022)

Active and Semi-Supervised Graph Neural Networks for Graph Classification. - Yu Xie; Shengze Lv; Yuhua Qian; Chao Wen; Jiye Liang (IEEE Trans. Big Data, 2022)

Dynamic Heterogeneous-Graph Reasoning with Language Models and Knowledge Representation Learning for Commonsense Question Answering. - Yujie Wang 003; Hu Zhang 003; Jiye Liang; Ru Li 001 (ACL (1), 2023)

Swap-Reconstruction Autoencoder for Compositional Zero-Shot Learning. - Ting Guo; Jiye Liang; Guo-Sen Xie (ICME, 2023)

A General Representation Learning Framework with Generalization Performance Guarantees. - Junbiao Cui; Jianqing Liang; Qin Yue 002; Jiye Liang (ICML, 2023)

How Powerful are Shallow Neural Networks with Bandlimited Random Weights? - Ming Li 065; Sho Sonoda; Feilong Cao; Yu Guang Wang 001; Jiye Liang (ICML, 2023)

Set-membership Belief State-based Reinforcement Learning for POMDPs. - Wei Wei 018; Lijun Zhang; Lin Li 090; Huizhong Song; Jiye Liang (ICML, 2023)

Graph Neural Networks with Interlayer Feature Representation for Image Super-Resolution. - Shenggui Tang; Kaixuan Yao; Jianqing Liang; Zhiqiang Wang 005; Jiye Liang (WSDM, 2023)

A trilevel analysis of uncertainty measuresin partition-based granular computing. - Baoli Wang; Jiye Liang; Yiyu Yao (Artif. Intell. Rev., 2023)

PipeOptim: Ensuring Effective 1F1B Schedule with Optimizer-Dependent Weight Prediction. - Lei Guan; Dongsheng Li; Jiye Liang; Wenjian Wang; Xicheng Lu (CoRR, 2023)

Group-wise interactive region learning for zero-shot recognition. - Ting Guo; Jiye Liang; Guo-Sen Xie (Inf. Sci., 2023)

Corrigendum to "Weak multi-label learning with missing labels via instance granular discrimination" [Inform. Sci. 594 (2022) 200-216]. - Anhui Tan; Xiaowan Ji; Jiye Liang; Yuzhi Tao; Wei-Zhi Wu 001; Witold Pedrycz (Inf. Sci., 2023)

A new contrastive learning framework for reducing the effect of hard negatives. - Wentao Cui; Liang Bai; Xian Yang 001; Jiye Liang (Knowl. Based Syst., 2023)

Generalization Performance of Pure Accuracy and its Application in Selective Ensemble Learning. - Jieting Wang; Yuhua Qian; Feijiang Li; Jiye Liang; Qingfu Zhang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Hybrid sampling-based contrastive learning for imbalanced node classification. - Caixia Cui; Jie Wang 046; Wei Wei 018; Jiye Liang (Int. J. Mach. Learn. Cybern., 2023)

Unsupervised Dimensionality Reduction Based on Fusing Multiple Clustering Results. - Wei Wei 018; Qin Yue 002; Kai Feng; Junbiao Cui; Jiye Liang (IEEE Trans. Knowl. Data Eng., 2023)

Multiple metric learning via local metric fusion. - Xinyao Guo; Lin Li 090; Chuangyin Dang; Jiye Liang; Wei Wei 018 (Inf. Sci., 2023)

Self-Constrained Spectral Clustering. - Liang Bai; Jiye Liang; Yunxiao Zhao (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

High-order graph attention network. - Liancheng He; Liang Bai; Xian Yang 001; Hangyuan Du; Jiye Liang (Inf. Sci., 2023)

Spectral clustering with robust self-learning constraints. - Liang Bai; Minxue Qi; Jiye Liang (Artif. Intell., 2023)

Coupling learning for feature selection in categorical data. - Feng Wang 038; Jiye Liang; Peng Song 004 (Int. J. Mach. Learn. Cybern., 2023)

A bi-level metric learning framework via self-paced learning weighting. - Jing Yan; Wei Wei 018; Xinyao Guo; Chuangyin Dang; Jiye Liang (Pattern Recognit., 2023)

Evaluating Classification Model Against Bayes Error Rate. - Qingqiang Chen; Fuyuan Cao; Ying Xing; Jiye Liang (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Random Deep Graph Matching. - Yu Xie; Zhiguo Qin; Maoguo Gong; Bin Yu 011; Jiye Liang (IEEE Trans. Knowl. Data Eng., 2023)

Local Causal Discovery in Multiple Manipulated Datasets. - Yunxia Wang; Fuyuan Cao; Kui Yu; Jiye Liang (IEEE Trans. Neural Networks Learn. Syst., 2023)

Multi-actor mechanism for actor-critic reinforcement learning. - Lin Li 090; Yuze Li; Wei Wei 018; Yujia Zhang; Jiye Liang (Inf. Sci., 2023)

Exploring the role of edge distribution in graph convolutional networks. - Liancheng He; Liang Bai; Xian Yang 001; Zhuomin Liang; Jiye Liang (Neural Networks, 2023)

Long and Short-Range Dependency Graph Structure Learning Framework on Point Cloud. - Jiye Liang; Zijin Du; Jianqing Liang; Kaixuan Yao; Feilong Cao (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Towards Privacy-Aware Causal Structure Learning in Federated Setting. - Jianli Huang; Xianjie Guo; Kui Yu; Fuyuan Cao; Jiye Liang (IEEE Trans. Big Data, 2023)

FRVA: Fact-Retrieval and Verification Augmented Entailment Tree Generation for Explainable Question Answering. - Yue Fan; Hu Zhang 003; Ru Li 001; Yujie Wang 003; Hongye Tan; Jiye Liang (ACL (Findings), 2024)

InstructEd: Soft-Instruction Tuning for Model Editing with Hops. - Xiaoqi Han; Ru Li 001; Xiaoli Li 001; Jiye Liang; Zifang Zhang; Jeff Z. Pan (ACL (Findings), 2024)

Hyperspherical Multi-Prototype with Optimal Transport for Event Argument Extraction. - Guangjun Zhang; Hu Zhang 003; Yujie Wang 003; Ru Li 001; Hongye Tan; Jiye Liang (ACL (1), 2024)

AGR: Reinforced Causal Agent-Guided Self-explaining Rationalization. - Yunxiao Zhao; Zhiqiang Wang 005; Xiaoli Li 001; Jiye Liang; Ru Li 001 (ACL (Short Papers), 2024)

Graph External Attention Enhanced Transformer. - Jianqing Liang; Min Chen; Jiye Liang (ICML, 2024)

Improving Generalization in Offline Reinforcement Learning via Adversarial Data Splitting. - Da Wang; Lin Li 090; Wei Wei 018; Qixian Yu; Jianye Hao; Jiye Liang (ICML, 2024)

Uncertainty-Aware Multi-view Learning for Prostate Cancer Grading with DWI. - Zhicheng Dong 001; Xiaodong Yue; Yufei Chen 002; Xujing Zhou; Jiye Liang (MICCAI (10), 2024)

SpeAr: A Spectral Approach for Zero-Shot Node Classification. - Ting Guo; Da Wang; Jiye Liang; Kaihan Zhang; Jianchao Zeng 001 (NeurIPS, 2024)

Scalable Constrained Policy Optimization for Safe Multi-agent Reinforcement Learning. - Lijun Zhang; Lin Li 090; Wei Wei 018; Huizhong Song; Yaodong Yang 001; Jiye Liang (NeurIPS, 2024)

Towards Effective Graph Rationalization via Boosting Environment Diversity. - Yujie Wang 003; Kui Yu; Yuhong Zhang 002; Fuyuan Cao; Jiye Liang (CoRR, 2024)

Controlling estimation error in reinforcement learning via Reinforced Operation. - Yujia Zhang; Lin Li 090; Wei Wei 018; Xiu You; Jiye Liang (Inf. Sci., 2024)

Resilient dynamic output feedback control for leader-following consensus of high-order uncertain multi-agent systems under sensor-actuator attacks. - Xiu You; Jiye Liang; Changchun Hua; Kuo Li 001 (J. Frankl. Inst., 2024)

A unified framework to control estimation error in reinforcement learning. - Yujia Zhang; Lin Li 090; Wei Wei 018; Yunpeng Lv; Jiye Liang (Neural Networks, 2024)

Discovering causally invariant features for out-of-distribution generalization. - Yujie Wang 003; Kui Yu; Guodu Xiang; Fuyuan Cao; Jiye Liang (Pattern Recognit., 2024)

Multi-view clustering via dynamic unified bipartite graph learning. - Xingwang Zhao; Shujun Wang; Xiaolin Liu; Jiye Liang (Pattern Recognit., 2024)

Heterogeneous-Graph Reasoning With Context Paraphrase for Commonsense Question Answering. - Yujie Wang 003; Hu Zhang 003; Jiye Liang; Ru Li 001 (IEEE ACM Trans. Audio Speech Lang. Process., 2024)

A zero-shot learning boosting framework via concept-constrained clustering. - Qin Yue 002; Junbiao Cui; Liang Bai; Jianqing Liang; Jiye Liang (Pattern Recognit., 2024)

Deep multi-view graph clustering network with weighting mechanism and collaborative training. - Jing Liu; Fuyuan Cao; Xuechun Jing; Jiye Liang (Expert Syst. Appl., 2024)

An incremental feature selection approach for dynamic feature variation. - Feng Wang 038; Xinhao Wang; Wei Wei 018; Jiye Liang (Neurocomputing, 2024)

Sparse regularized correlation filter for UAV object tracking with adaptive contextual learning and keyfilter selection. - Zhangjian Ji; Kai Feng; Yuhua Qian; Jiye Liang (Inf. Sci., 2024)

Efficient Classification by Removing Bayesian Confusing Samples. - Fuyuan Cao; Qingqiang Chen; Ying Xing; Jiye Liang (IEEE Trans. Knowl. Data Eng., 2024)

GUIDE: Training Deep Graph Neural Networks via Guided Dropout Over Edges. - Jie Wang 046; Jianqing Liang; Jiye Liang; Kaixuan Yao (IEEE Trans. Neural Networks Learn. Syst., 2024)

Advances of Pipeline Model Parallelism for Deep Learning Training: An Overview. - Lei Guan; Dong-Sheng Li; Jiye Liang; Wen-Jian Wang; Ke-shi Ge; Xicheng Lu (J. Comput. Sci. Technol., 2024)

Re-attentive experience replay in off-policy reinforcement learning. - Wei Wei 018; Da Wang; Lin Li 090; Jiye Liang (Mach. Learn., 2024)

Debiased graph contrastive learning based on positive and unlabeled learning. - Zhiqiang Li; Jie Wang 046; Jiye Liang (Int. J. Mach. Learn. Cybern., 2024)

Enhancing Drug Recommendations Via Heterogeneous Graph Representation Learning in EHR Networks. - Haijun Zhang; Xian Yang 001; Liang Bai; Jiye Liang (IEEE Trans. Knowl. Data Eng., 2024)

Learning Causal Chain Graph Structure via Alternate Learning and Double Pruning. - Shujing Yang; Fuyuan Cao; Kui Yu; Jiye Liang (IEEE Trans. Big Data, 2024)

Robust graph neural networks with Dirichlet regularization and residual connection. - Kaixuan Yao; Zijin Du; Ming Li 065; Feilong Cao; Jiye Liang (Int. J. Mach. Learn. Cybern., 2024)

Black-Box Adversarial Attack on Graph Neural Networks With Node Voting Mechanism. - Liangliang Wen; Jiye Liang; Kaixuan Yao; Zhiqiang Wang 005 (IEEE Trans. Knowl. Data Eng., 2024)

Adaptive Prototype Interaction Network for Few-Shot Knowledge Graph Completion. - Yuling Li 001; Kui Yu; Yuhong Zhang 002; Jiye Liang; Xindong Wu 001 (IEEE Trans. Neural Networks Learn. Syst., 2024)

Graph Regulation Network for Point Cloud Segmentation. - Zijin Du; Jianqing Liang; Jiye Liang; Kaixuan Yao; Feilong Cao (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Causal Discovery From Unknown Interventional Datasets Over Overlapping Variable Sets. - Fuyuan Cao; Yunxia Wang; Kui Yu; Jiye Liang (IEEE Trans. Knowl. Data Eng., 2024)

Progressive Skeleton Learning for Effective Local-to-Global Causal Structure Learning. - Xianjie Guo; Kui Yu; Lin Liu 003; Jiuyong Li; Jiye Liang; Fuyuan Cao; Xindong Wu 001 (IEEE Trans. Knowl. Data Eng., 2024)

K-Relations-Based Consensus Clustering With Entropy-Norm Regularizers. - Liang Bai; Jiye Liang (IEEE Trans. Neural Networks Learn. Syst., 2024)

Graph Segmentation and Contrastive Enhanced Explainer for Graph Neural Networks. - Zhiqiang Wang 005; Jiayu Guo; Jianqing Liang; Jiye Liang; Shiying Cheng; Jiarong Zhang (AAAI, 2025)

Label Noise Correction via Fuzzy Learning Machine. - Jiye Liang; Yixiao Li; Junbiao Cui (AAAI, 2025)

GNN-Transformer Cooperative Architecture for Trustworthy Graph Contrastive Learning. - Jianqing Liang; Xinkai Wei; Min Chen; Zhiqiang Wang 005; Jiye Liang (AAAI, 2025)

Improving Generalization in Offline Reinforcement Learning via Latent Distribution Representation Learning. - Da Wang; Lin Li 090; Wei Wei 018; Qixian Yu; Jianye Hao; Jiye Liang (AAAI, 2025)

Learning Textual Prompts for Open-World Semi-Supervised Learning. - Yuxin Fan; Junbiao Cui; Jiye Liang (CVPR, 2025)

Hyperbolic Multi-Criteria Rating Recommendation. - Zhihao Guo; Ting Han 001; Peng Song 004; Chenjiao Feng; Kaixuan Yao; Jiye Liang (SIGIR, 2025)

Hawkes Point Process-enhanced Dynamic Graph Neural Network. - Zhiqiang Wang 005; Baijing Hu; Kaixuan Yao; Jiye Liang (WSDM, 2025)

Federated local causal structure learning. - Kui Yu; Chen Rong; Hao Wang 008; Fuyuan Cao; Jiye Liang (Sci. China Inf. Sci., 2025)

Chain graphs structure learning given local background knowledge. - Shujing Yang; Fuyuan Cao; Kui Yu; Jiye Liang (Int. J. Approx. Reason., 2025)

Enhancing few-shot KB-VQA with panoramic image captions guided by Large Language Models. - Pengpeng Qiang; Hongye Tan; Xiaoli Li 001; Dian Wang 006; Ru Li 001; Xinyi Sun; Hu Zhang 003; Jiye Liang (Neurocomputing, 2025)

Multi-View Fusion Graph Attention Network for Multilabel Class Incremental Learning. - Anhui Tan; Yu Wang 106; Wei-Zhi Wu 001; Weiping Ding 001; Jiye Liang (Inf. Fusion, 2025)

Weakly-supervised explainable question answering via question aware contrastive learning and adaptive gate mechanism. - Yue Fan; Hu Zhang 003; Ru Li 001; Yujie Wang 003; Guangjun Zhang; Hongye Tan; Jiye Liang (Inf. Sci., 2025)

Rethinking exploration-exploitation trade-off in reinforcement learning via cognitive consistency. - Da Wang; Wei Wei 018; Lin Li 090; Xin Wang; Jiye Liang (Neural Networks, 2025)

Learning robust MLPs on graphs via cross-layer distillation from a causal perspective. - Hangyuan Du; Wenjian Wang; Weihong Zhang; Dengke Su; Liang Bai; Lu Bai; Jiye Liang (Pattern Recognit., 2025)

Image dehazing via self-supervised depth guidance. - Yudong Liang; Shaoji Li; De Cheng; Wenjian Wang; Deyu Li; Jiye Liang (Pattern Recognit., 2025)

TSI-GCN: Translation and scaling invariant GCN for 3D point cloud analysis. - Zijin Du; Jiye Liang; Kaixuan Yao; Feilong Cao (Pattern Recognit. Lett., 2025)

A motif based hypergraph multi-level semantic encoding framework for social recommender systems. - Hangyuan Du; Wenjian Wang; Liang Bai; Lu Bai; Jiye Liang (Signal Process., 2025)

PAH2T-Former: Paired-Attention Hybrid Hierarchical Transformer for Synergistically Enhanced FMT Reconstruction Quality and Efficiency. - Peng Zhang 078; Xingyu Liu; Qianqian Xue; Yu Shang; Chen Liu; Ruhao Chen; Honglei Gao; Jiye Liang; Wenjian Wang; Guanglei Zhang (IEEE Trans. Computational Imaging, 2025)

Graph Contrastive Learning for Fusion of Graph Structure and Attribute Information. - Zhuomin Liang; Liang Bai; Xian Yang 001; Jiye Liang (IEEE Trans. Multim., 2025)

Contrastive Learning With Enhancing Detailed Information for Pre-Training Vision Transformer. - Zhuomin Liang; Liang Bai; Jinyu Fan; Xian Yang 001; Jiye Liang (IEEE Trans. Circuits Syst. Video Technol., 2025)

Improving Image Contrastive Clustering Through Self-Learning Pairwise Constraints. - Yecheng Guo; Liang Bai; Xian Yang 001; Jiye Liang (IEEE Trans. Neural Networks Learn. Syst., 2025)

C-LoRA: Continual Low-Rank Adaptation for Pre-trained Models. - Xin Zhang; Liang Bai; Xian Yang 001; Jiye Liang (CoRR, 2025)

FWCEC: An Enhanced Feature Weighting Method via Causal Effect for Clustering. - Fuyuan Cao; Xuechun Jing; Kui Yu; Jiye Liang (IEEE Trans. Knowl. Data Eng., 2025)

RSS-Bagging: Improving Generalization Through the Fisher Information of Training Data. - Jieting Wang; Feijiang Li; Jue Li; Chenping Hou; Yuhua Qian; Jiye Liang (IEEE Trans. Neural Networks Learn. Syst., 2025)

CM-CaFE: A Clustering Method with Causality-based Feature Embedding. - Xuechun Jing; Fuyuan Cao; Kui Yu; Jiye Liang (ACM Trans. Knowl. Discov. Data, 2025)

PipeOptim: Ensuring Effective 1F1B Schedule With Optimizer-Dependent Weight Prediction. - Lei Guan; Dongsheng Li 001; Yongle Chen; Jiye Liang; Wenjian Wang; Xicheng Lu (IEEE Trans. Knowl. Data Eng., 2025)

A Survey of Continual Reinforcement Learning. - Chaofan Pan; Xin Yang 012; Yanhua Li; Wei Wei 018; Tianrui Li 001; Bo An 001; Jiye Liang (CoRR, 2025)

An efficient Bayes error rate estimation method. - Qingqiang Chen; Fuyuan Cao; Ying Xing; Jiye Liang (Mach. Learn., 2025)

Summary Graph Induced Invariant Learning for Generalizable Graph Learning. - Xuecheng Ning; Yujie Wang 003; Kui Yu; Jiali Miao; Fuyuan Cao; Jiye Liang (IEEE Trans. Knowl. Data Eng., 2025)

Positive region preserved random sampling: an efficient feature selection method for massive data. - Hexiang Bai; Deyu Li; Jiye Liang; Yanhui Zhai (CoRR, 2025)

Prompting Large Language Models with Partial Knowledge for Answering Questions with Unseen Entities. - Zhichao Yan; Jiapu Wang; Jiaoyan Chen 001; Yanyan Wang; Hongye Tan; Jiye Liang; Xiaoli Li 001; Ru Li 001; Jeff Z. Pan (CoRR, 2025)

Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies. - Yi Ma 005; Hongyao Tang; Chenjun Xiao; Yaodong Yang 001; Wei Wei 018; Jianye Hao; Jiye Liang (CoRR, 2025)

Multi-Channel Disentangled Graph Neural Networks With Different Types of Self-Constraints. - Zhuomin Liang; Liang Bai; Xian Yang 001; Jiye Liang (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Partial Multilabel Learning via Dynamic Fuzzy Aggregations of Multigranularity Features. - Anhui Tan; Jianhang Xu; Weizhi Wu 001; Weiping Ding 001; Jiye Liang (IEEE Trans. Fuzzy Syst., 2025)

Causal inference for alleviating confounding bias in multi-criteria rating recommendation. - Zhihao Guo; Peng Song 004; Chenjiao Feng; Kaixuan Yao; Jiye Liang (Inf. Process. Manag., 2026)